diff --git a/.github/workflows/main.yml b/.github/workflows/main.yml new file mode 100644 index 0000000000000000000000000000000000000000..09a0f6187e58c1e5a84c6512001da1c4a863a4da --- /dev/null +++ b/.github/workflows/main.yml @@ -0,0 +1,20 @@ +name: Sync to Hugging Face hub +on: + push: + branches: [main] + + # to run this workflow manually from the Actions tab + workflow_dispatch: + +jobs: + sync-to-hub: + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@v3 + with: + fetch-depth: 0 + lfs: true + - name: Push to hub + env: + HF_TOKEN: ${{ secrets.HF_TOKEN }} + run: git push https://shaocongma:$HF_TOKEN@huggingface.co/spaces/shaocongma/auto-draft main diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000000000000000000000000000000000000..85e7c1dfcb7fbb33f932c81024018cd8c10519da --- /dev/null +++ b/.gitignore @@ -0,0 +1 @@ +/.idea/ diff --git a/.idea/.gitignore b/.idea/.gitignore new file mode 100644 index 0000000000000000000000000000000000000000..c21fa44c31a127f3fb1b705cf55f56b0b059eb1d --- /dev/null +++ b/.idea/.gitignore @@ -0,0 +1,10 @@ +# Default ignored files +/shelf/ +/workspace.xml +# Datasource local storage ignored files +/dataSources/ +/dataSources.local.xml +# Editor-based HTTP Client requests +/httpRequests/ +**/__pycache__ +**/.idea diff --git a/.idea/auto-draft.iml b/.idea/auto-draft.iml new file mode 100644 index 0000000000000000000000000000000000000000..8e5446ac9594d6e198c2a2923123566d13b94bf9 --- /dev/null +++ b/.idea/auto-draft.iml @@ -0,0 +1,14 @@ + + + + + + + + + + + + \ No newline at end of file diff --git a/.idea/inspectionProfiles/Project_Default.xml b/.idea/inspectionProfiles/Project_Default.xml new file mode 100644 index 0000000000000000000000000000000000000000..a37f689457fcc22d65dc04286276ea7811857f0c --- /dev/null +++ b/.idea/inspectionProfiles/Project_Default.xml @@ -0,0 +1,95 @@ + + + + \ No newline at end of file diff --git a/.idea/inspectionProfiles/profiles_settings.xml b/.idea/inspectionProfiles/profiles_settings.xml new file mode 100644 index 0000000000000000000000000000000000000000..105ce2da2d6447d11dfe32bfb846c3d5b199fc99 --- /dev/null +++ b/.idea/inspectionProfiles/profiles_settings.xml @@ -0,0 +1,6 @@ + + + + \ No newline at end of file diff --git a/.idea/misc.xml b/.idea/misc.xml new file mode 100644 index 0000000000000000000000000000000000000000..400aa670e8dd350d9126705a47462743cb6e04ab --- /dev/null +++ b/.idea/misc.xml @@ -0,0 +1,4 @@ + + + + \ No newline at end of file diff --git a/.idea/modules.xml b/.idea/modules.xml new file mode 100644 index 0000000000000000000000000000000000000000..096ee2bfc78b161803a55a896c9aca8875357f6c --- /dev/null +++ b/.idea/modules.xml @@ -0,0 +1,8 @@ + + + + + + + + \ No newline at end of file diff --git a/.idea/vcs.xml b/.idea/vcs.xml new file mode 100644 index 0000000000000000000000000000000000000000..94a25f7f4cb416c083d265558da75d457237d671 --- /dev/null +++ b/.idea/vcs.xml @@ -0,0 +1,6 @@ + + + + + + \ No newline at end of file diff --git a/04c9a7bee23cedb969f454f79837c0e3.zip b/04c9a7bee23cedb969f454f79837c0e3.zip new file mode 100644 index 0000000000000000000000000000000000000000..c1d40102abd55c46ae8dbb7e34f289bf23e91cdc Binary files /dev/null and b/04c9a7bee23cedb969f454f79837c0e3.zip differ diff --git a/6d732fcb-0516-11ee-9128-085bd609d2a0.json b/6d732fcb-0516-11ee-9128-085bd609d2a0.json new file mode 100644 index 0000000000000000000000000000000000000000..1ef5938b6a34a45b906571a8702f8391e71b9d89 --- /dev/null +++ b/6d732fcb-0516-11ee-9128-085bd609d2a0.json @@ -0,0 +1 @@ +{"wang2022hybrid": {"paper_id": "wang2022hybrid", "title": "Hybrid Event-Based Leader-Following Consensus of Nonlinear Multiagent Systems With Semi-Markov Jump Parameters", "abstract": "This article aims to systematically address the leader-following consensus issue for continuous-time multiagent systems with semi-Markov jump parameters. A more universal random process, semi-Markov process, is utilized to model the variations of parameters which may result from the complexity of environment. The innovative hybrid event-triggered strategy associated with an improved threshold function is employed for economizing the network bandwidth resources. It presents an exponential decay term in the threshold function for decreasing the transmission frequency of superfluous data packets, ulteriorly reducing triggering times. The dominating core concentrates on the design of a controller interrelated with the hybrid event-triggered condition, which can be implemented to ensure the leader-following consensus of the considered systems. On the strength of time-dependent and piecewise Lyapunov\u2013Krasovskii functional, several criteria, which are capable of ensuring the leader-following consensus of the multiagent systems, are derived. Ultimately, two suitable numerical examples and a meaningful practical one are utilized to demonstrate the validity and potential of the derived results.", "link": "dblp.org/rec/journals/sj/WangWYCS22", "authors": "Jing Wang and Yuanshang Wang and Huaicheng Yan and Jinde Cao and Hao Shen", "year": "2022", "journal": "IEEE Systems Journal", "embeddings": [-2.5333690643310547, -2.64697265625, -0.6855220198631287, 4.313614845275879, -4.072737216949463, -1.6031031608581543, 1.0752400159835815, -3.5918147563934326, 2.8573360443115234, -3.1439056396484375, 0.7007471323013306, 0.669966459274292, -1.8064043521881104, -3.90265154838562, -4.257413864135742, 0.33556923270225525, 0.1890839785337448, 2.8932058811187744, -0.6093538403511047, -1.4667457342147827, -5.377668380737305, 4.763171195983887, -5.237687587738037, -5.2121901512146, -1.605357050895691, -3.3704261779785156, 3.7928695678710938, -1.0472744703292847, 1.9704824686050415, -1.6008861064910889, -1.2712249755859375, -1.9832268953323364, 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-5.289212226867676]}, "li2016consensus": {"paper_id": "li2016consensus", "title": "Consensus of Multiagent Systems and Synchronization of Complex Networks: A Unified Viewpoint", "abstract": "A distributed observer-type consensus protocol based on relative output measurements is proposed and a new framework is introduced to address in a unified way the consensus of multiagent systems and the synchronization of complex networks.", "link": "dblp.org/rec/journals/tcas/LiDCH10", "authors": "Zhongkui Li and Z. 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address the proposed synthesis problem of the containment control with respect to continuous-time semi- Markovian multiagent systems with semi-Markovian switching topologies.", "link": "dblp.org/rec/journals/tsmc/LiangZSH21", "authors": "Hongjing Liang and Linchuang Zhang and Yonghui Sun and Tingwen Huang", "year": "2021", "journal": "IEEE Transactions on Systems, Man, and Cybernetics: Systems", "embeddings": [-2.8364439010620117, -1.0587234497070312, 1.1553621292114258, 2.8478007316589355, -1.3025730848312378, -2.5863611698150635, 3.2094476222991943, -4.249463081359863, 6.4152607917785645, -4.954710006713867, 4.2190351486206055, 1.0923829078674316, -2.2185888290405273, -4.135825157165527, -3.19683837890625, 2.5250730514526367, 1.3960351943969727, 2.796215534210205, -2.6912620067596436, 0.7849596738815308, -4.153141021728516, 4.936430931091309, -8.433985710144043, -2.992737054824829, -0.5455065965652466, -2.892824172973633, 5.443358421325684, 0.4447971284389496, 4.2616400718688965, 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-0.10589820146560669, -1.9922232627868652, -7.136540412902832]}, "li2021adaptive": {"paper_id": "li2021adaptive", "title": "Adaptive Multigradient Recursive Reinforcement Learning Event-Triggered Tracking Control for Multiagent Systems", "abstract": "A new lemma about the relative threshold event-triggered control strategy is proposed to handle the compensation error, which can improve the utilization of communication resources and weaken the negative impact on tracking accuracy and closed-loop system stability.", "link": "dblp.org/rec/journals/tnn/LiWCL23", "authors": "Hongyi Li and Ying Wu and Mou Chen and Renquan Lu", "year": "2021", "journal": "IEEE Transactions on Neural Networks and Learning Systems", "embeddings": [-3.2281479835510254, -1.2503504753112793, 0.9372493028640747, 6.994015216827393, -2.487520217895508, -2.5356552600860596, 0.9453625679016113, -3.0047242641448975, 0.6388940811157227, -2.051173210144043, 0.4735206961631775, 2.361691951751709, -1.1669203042984009, 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Sixteen chapters are organized in four main parts: Introductory Papers; Multiagent Based Supply Chain Modeling; Collaboration and Coordination Between Agents in a Supply Chain; and Multiagent Based Supply Chain Management: Applications. The result is a comprehensive review of existing literature, and ideas for future research. PAAMS, the International Conference on Practical Applications of Agents and Multi-Agent Systems is an evolution of the International Workshop on Practical Applications of Agents and Multi-Agent Systems. PAAMS is an international yearly tribune to present, to discuss, and to disseminate the latest developments and the most important outcomes related to real-world applications. It provides a unique opportunity to bring multi-disciplinary experts, academics and practitioners together to exchange their experience in the development of Agents and Multi-Agent Systems. This volume presents the papers that have been accepted for the 2011 in the workshops: Workshop on Agents for Ambient Assisted Living, Workshop on Agent-Based", "link": "", "authors": "", "year": "2021", "journal": "arXiv preprint", "embeddings": [-3.8515477180480957, -1.481959342956543, 0.11438106000423431, 5.6574625968933105, -4.79820442199707, -1.068315863609314, 1.230405569076538, -1.9623253345489502, 0.34036993980407715, -1.0031523704528809, 1.437497854232788, 2.15714693069458, -4.671563148498535, -1.9620087146759033, -1.6334009170532227, 0.28877708315849304, 4.541170597076416, -2.331009864807129, 4.425687789916992, 0.18603220582008362, -2.5305562019348145, 5.767736434936523, -3.4296741485595703, -4.930832862854004, 3.0787439346313477, -2.069844961166382, 4.950916290283203, -1.3551543951034546, 2.22173810005188, 1.1803418397903442, -1.9721521139144897, -2.2399773597717285, 3.6978516578674316, -2.8290317058563232, 3.2168467044830322, -8.203666687011719, -4.52904748916626, 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Multiagent Systems", "abstract": "It is mathematically proved that the followers\u2019 states can track the leader\u2019s trajectory within predefined time and the settling time bound is directly related to tunable parameters, which facilitates the control protocol design to meet the desired convergence time requirement.", "link": "dblp.org/rec/journals/tsmc/NiLTL21", "authors": "Junkang Ni and Ling Liu and Yang Tang and Chongxin Liu", "year": "2021", "journal": "IEEE Transactions on Systems, Man, and Cybernetics: Systems", "embeddings": [-4.849780559539795, -3.4104671478271484, 3.0483558177948, 6.146744728088379, -7.47050666809082, -0.7929101586341858, 7.791528701782227, -3.2607667446136475, 4.64752197265625, -2.7262213230133057, 0.7917410731315613, 0.83545982837677, -2.0018696784973145, -3.3431570529937744, -5.633307456970215, 1.8795794248580933, -0.7930627465248108, -1.7583869695663452, 1.6212109327316284, -1.318464756011963, -3.7127366065979004, 6.988791465759277, 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eigenvector of Laplacian matrix is utilized to construct a novel Lyapunov functional.", "link": "dblp.org/rec/journals/tsmc/CuiLZA21", "authors": "Ying-liu Cui and Yurong Liu and Wenbing Zhang and F. Alsaadi", "year": "2021", "journal": "IEEE Transactions on Systems, Man, and Cybernetics: Systems", "embeddings": [-5.191415786743164, -3.2112345695495605, -0.5065202713012695, 5.86868143081665, -5.757444381713867, -3.4807910919189453, 6.60872220993042, -7.675420761108398, 3.354999303817749, -4.4348578453063965, -2.720151901245117, 1.443469524383545, 1.9369709491729736, -6.0360589027404785, -4.441646575927734, -1.0422157049179077, -1.985547423362732, 1.8191392421722412, -2.8110899925231934, 1.14130437374115, -1.8502341508865356, 2.751669406890869, -7.479827404022217, -2.148197889328003, -1.1761112213134766, -2.4351425170898438, 2.419651508331299, -2.7145092487335205, 3.9684219360351562, -1.2880816459655762, -2.494593381881714, -3.9204511642456055, 4.782337188720703, -2.230375289916992, 4.051211357116699, -2.449716567993164, -0.9421522617340088, 3.4326629638671875, -0.7464266419410706, 1.4062917232513428, -2.3319549560546875, 1.6370794773101807, 0.733907163143158, -4.344843864440918, 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containment control scheme is proposed, which is conditionally updated only at the sampled instants and it is proved that all signals in the closed-loop system are semiglobally uniformly ultimately bounded.", "link": "dblp.org/rec/journals/tfs/0002W0021", "authors": "Qi Zhou and Wei Wang and Hui Ma and Hongyi Li", "year": "2021", "journal": "IEEE transactions on fuzzy systems", "embeddings": [-2.367823362350464, -1.9710276126861572, 2.2480854988098145, 5.221753120422363, -0.3445468842983246, -4.218194484710693, 3.275949716567993, -4.4182329177856445, 3.1334733963012695, -5.560958385467529, 2.3257253170013428, 2.454892873764038, -3.0513076782226562, -5.35124397277832, -3.8757920265197754, 2.3758726119995117, -2.976101875305176, 2.987375020980835, -0.9819194078445435, -1.407131552696228, -3.145476818084717, 3.267939329147339, -7.248395919799805, -4.333238124847412, -1.2670345306396484, -1.0763232707977295, 4.706193923950195, -0.9771451950073242, 3.8807671070098877, 1.9550938606262207, 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"zhang2022deadline": {"paper_id": "zhang2022deadline", "title": "Deadline-Aware Dynamic Task Scheduling in Edge\u2013Cloud Collaborative Computing", "abstract": "A dynamic time-sensitive scheduling algorithm with greedy strategy (TSGS) that ranks server capability and job size in a hybrid and hierarchical scenario is proposed and is proposed to employ comprehensive execution capability (CEC) to measure the performance of a server for the first time and perform effective server load balancing while satisfying the user\u2019s requirement for tasks.", "link": "", "authors": "Yu Zhang and B. Tang and Jincheng Luo and Jiaming Zhang", "year": "2022", "journal": "Electronics", "embeddings": [-1.7923510074615479, -3.0062787532806396, -1.8254990577697754, 6.690145015716553, 0.45287635922431946, -0.5751716494560242, 2.4513065814971924, -2.989755868911743, -1.1406300067901611, -1.996500015258789, 1.9405597448349, 1.8868606090545654, 0.17281734943389893, -5.6755290031433105, -3.4768552780151367, 0.6206318736076355, -2.1404199600219727, 2.80680513381958, 3.4716625213623047, 1.469049096107483, -3.1024487018585205, 3.324531316757202, -1.7497457265853882, -0.713111937046051, -1.2122780084609985, -2.643092632293701, 3.469796657562256, -0.27558058500289917, 0.032264452427625656, -5.2976603507995605, -0.7151262760162354, -0.8949783444404602, 4.728091239929199, -1.4034751653671265, 5.255385875701904, -5.796329021453857, -3.5235493183135986, 4.764956951141357, -0.7918192744255066, 4.059126853942871, 2.229625940322876, 3.146674871444702, -1.1787399053573608, -3.2763211727142334, 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edge\u2010cloud collaboration, which helps understand the challenges faced by edge\u2010 cloud collaborative computing, is introduced.", "link": "dblp.org/rec/journals/ijis/YangZZCWL22", "authors": "Jie Yang and Jun Zheng and Zheng Zhang and Qi Chen and Duncan S. Wong and Yuan-zhang Li", "year": "2022", "journal": "International Journal of Intelligent Systems", "embeddings": [-3.418736219406128, -3.40521240234375, -1.6764219999313354, 9.443954467773438, -2.2095847129821777, -3.8141329288482666, 3.759866237640381, -6.2842698097229, -1.9699918031692505, -3.9290785789489746, -0.9218121767044067, 2.68485689163208, 6.15015983581543, -6.386749267578125, -2.493635416030884, -1.0959841012954712, -6.2529449462890625, -2.546670436859131, 0.39899688959121704, 1.9281399250030518, -1.9236421585083008, 2.303671360015869, 0.23914623260498047, 2.418785572052002, 1.7437472343444824, -0.4563121497631073, 3.8830554485321045, -1.9924135208129883, 2.7114059925079346, -3.6732559204101562, 0.5817644596099854, -5.707704544067383, 3.448246479034424, 0.5674749612808228, 3.703099012374878, -5.456358909606934, -1.0586549043655396, 5.256208419799805, -7.217995643615723, 4.6298017501831055, -1.2332829236984253, 0.6521228551864624, -0.3784272074699402, -0.7925673127174377, 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production is proposed and the effectiveness of the proposed TCCD method is verified by using the prototype platform of personalized product packaging intelligent production line with the same process flow.", "link": "dblp.org/rec/journals/access/JiangW21", "authors": "Chun Jiang and J. Wan", "year": "2021", "journal": "IEEE Access", "embeddings": [-5.595178127288818, -6.34743070602417, -2.3188419342041016, 4.45997953414917, 1.3206498622894287, 1.1964521408081055, -0.04175958037376404, -5.02025842666626, -0.9203643202781677, -3.037527561187744, -0.2193615734577179, 0.7662281394004822, 0.933198094367981, -2.5553219318389893, -3.667285442352295, 1.8565945625305176, -0.020317018032073975, 0.4208296835422516, 3.345004081726074, -2.004678726196289, -2.2968645095825195, 5.460152626037598, -2.4077305793762207, 2.7973508834838867, 3.940070152282715, 1.3506673574447632, 2.8531200885772705, -1.6515617370605469, 1.1834344863891602, -7.49061393737793, 1.3030740022659302, -2.256002426147461, 4.988239765167236, 1.3983285427093506, 4.899844169616699, -6.590305328369141, -4.697292327880859, 2.6784024238586426, -0.599980354309082, 1.73482084274292, 3.387794017791748, -0.6928130388259888, 2.6695687770843506, 1.2268364429473877, -2.098461627960205, -1.6429396867752075, 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efficiently and supports an iterative way for model evolution and updating so as to enable the AIeT applications agile and data-driven.", "link": "dblp.org/rec/journals/jcloudc/RongXTF21", "authors": "Gu Rong and Yangchen Xu and Xinxin Tong and Hao Fan", "year": "2021", "journal": "J. 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reinforcement learning is utilized to obtain long-term benefits.", "link": "", "authors": "Tao Leng and Xiaoyao Li and Dongwei Hu and Gaofeng Cui and Weidong Wang", "year": "2021", "journal": "Wireless Communications and Mobile Computing", "embeddings": [-3.750231981277466, -0.7445201873779297, -4.107653617858887, 6.8645100593566895, 0.30078867077827454, -2.4059197902679443, 2.0816240310668945, -8.3436861038208, 0.502692699432373, -3.9209556579589844, 2.465533494949341, 1.6592397689819336, 1.4859310388565063, -4.110386848449707, -2.4522061347961426, -0.08155359327793121, -1.3821715116500854, -0.08521533012390137, 2.147458076477051, 1.7188940048217773, -5.255231857299805, 3.3564460277557373, -2.0284202098846436, -0.25773489475250244, -1.1809405088424683, -0.7779877781867981, 0.6371220350265503, 2.2561206817626953, -0.10865538567304611, -6.383838653564453, -0.3653636574745178, -3.9220998287200928, 4.737969398498535, 2.017731189727783, 6.129367828369141, -5.848926544189453, 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Collaborative Computing Approach for Mobile Web Augmented Reality in 5G Networks", "abstract": "This article proposes the first edge-based collaborative object recognition solution for mobile Web AR in the 5G era with finegrained and adaptive DNN partitioning for the collaboration between the cloud, the edge, and the mobile Web browser and proposes a differentiated DNN computation scheduling approach specially designed for the edge platform.", "link": "dblp.org/rec/journals/network/RenQHLDC20", "authors": "Pei Ren and Xiuquan Qiao and Yakun Huang and Ling Liu and S. Dustdar and Junliang Chen", "year": "2020", "journal": "IEEE Network", "embeddings": [-5.716434478759766, -4.5775370597839355, -2.903010845184326, 6.4719038009643555, -0.5431984663009644, -0.4927707612514496, 1.7531161308288574, -2.2128987312316895, -1.900956392288208, -1.3758591413497925, -1.2554328441619873, 1.3211688995361328, 1.3657819032669067, -5.375938415527344, -3.944119453430176, -0.9593124389648438, -2.344297170639038, -2.364278554916382, 1.5936033725738525, -1.0149195194244385, -1.702136754989624, 1.5960066318511963, -2.99184513092041, 1.0877158641815186, -0.3492114543914795, -0.3700093626976013, -0.731633722782135, 3.8527798652648926, 0.7904611825942993, -3.602043867111206, -0.26673629879951477, -3.7939045429229736, 6.83406925201416, 0.008664965629577637, 3.5131947994232178, -1.6682722568511963, -1.9842965602874756, 2.7432873249053955, -2.4643375873565674, -4.002867698669434, 5.816850662231445, 4.902705669403076, -2.463484525680542, -0.9896308183670044, 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prescheduling the computation side for each task from a global perspective is designed.", "link": "dblp.org/rec/journals/access/GaoHHY20", "authors": "Zihan Gao and Wanming Hao and Zhuo Han and Shou-yi Yang", "year": "2020", "journal": "IEEE Access", "embeddings": [-5.223189353942871, -2.034728765487671, -4.41092586517334, 8.078417778015137, -1.5428173542022705, -0.1215897798538208, 2.02561354637146, -6.507757186889648, -1.238096833229065, -3.462780237197876, -0.41237545013427734, 2.4202380180358887, 0.3417820930480957, -3.995542526245117, -1.299164056777954, 0.6459013819694519, -1.9556941986083984, 0.06144803762435913, 3.7326080799102783, 2.8263392448425293, -2.865114450454712, 1.5121670961380005, -5.1532135009765625, -0.06265115737915039, 0.9317243695259094, -1.4950146675109863, 1.9494130611419678, 0.27932220697402954, -1.0175576210021973, -4.812551498413086, -0.30922931432724, -3.418367862701416, 6.354538440704346, 1.6661043167114258, 6.1347479820251465, -4.050655841827393, 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Computational Latency-Based Pricing", "abstract": "This work considers the collaborative computing system where a user offloads the computation-intensive and latency-sensitive tasks to multiple idle computing devices by a centralized computing sharing platform (CSP) and proposes a computational latency-based pricing mechanism from the perspective of the quality-of-experience performance.", "link": "dblp.org/rec/journals/tsusc/WangWZW20", "authors": "Qianqian Wang and Qin Wang and Hongbo Zhu and Xianbin Wang", "year": "2020", "journal": "IEEE Transactions on Sustainable Computing", "embeddings": [-4.731773853302002, -0.9880663156509399, -3.343430757522583, 5.8351922035217285, -1.2796441316604614, -2.081523895263672, 2.947596788406372, -6.647751808166504, 0.5051755905151367, -4.3259148597717285, 1.108372449874878, 0.5169949531555176, 4.087987422943115, -7.040252208709717, -2.8682026863098145, 0.40371182560920715, -4.451231956481934, -1.6291273832321167, 2.442758321762085, 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learning algorithm among the UEs, UAVs/BSs, and HCP to collaboratively predict the content caching placement by jointly considering traffic distribution, UE mobility and localized content popularity is proposed.", "link": "dblp.org/rec/journals/tetc/FadlullahK22", "authors": "Zubair Md. Fadlullah and N. Kato", "year": "2022", "journal": "IEEE Transactions on Emerging Topics in Computing", "embeddings": [-7.3006134033203125, -0.17618399858474731, -1.6970324516296387, 8.58006477355957, -2.1696863174438477, -2.3871636390686035, 4.577559471130371, -4.029959678649902, -0.1558350920677185, -2.780419111251831, 0.3523625135421753, -1.7693649530410767, 1.8827570676803589, -5.48062801361084, -5.607174396514893, -0.962637722492218, -3.180753707885742, 0.39073944091796875, 0.35593587160110474, 1.6047571897506714, -4.996065139770508, 3.0500240325927734, -1.6708827018737793, 0.44496655464172363, -0.6114063262939453, -2.816824197769165, 3.3240864276885986, 0.3327179551124573, 2.2812511920928955, -3.1513617038726807, -1.783498764038086, -3.3808977603912354, 6.599703311920166, 1.448002815246582, 4.392807960510254, -7.657724380493164, -4.962993621826172, 2.861900568008423, -4.052190780639648, 1.1843831539154053, 2.2673282623291016, -0.8230044841766357, -2.0174851417541504, -0.7440242767333984, 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are presented and analyzed, and it is proved that the proposed cloud-based control scheme renders the MAS stable and to achieve output consensus.", "link": "dblp.org/rec/journals/sj/YangWTYX22", "authors": "Yang Yang and Ailing Wang and Haoran Tan and Wenbin Yue and Aijia Xin", "year": "2022", "journal": "IEEE Systems Journal", "embeddings": [-1.421046257019043, -3.58846116065979, 0.4389553666114807, 8.383213996887207, -2.5173559188842773, -3.340409755706787, 5.0896406173706055, -3.187636613845825, 3.367514133453369, -3.3454575538635254, 1.1667295694351196, 1.9437932968139648, 0.6908031702041626, -4.623264312744141, -4.453292369842529, -0.24662891030311584, -1.4444730281829834, 1.7138421535491943, -0.12815767526626587, 0.4863363802433014, -4.198843002319336, 4.930873870849609, -3.683534860610962, -0.8037248849868774, -2.3833699226379395, -3.45145845413208, 2.706883668899536, 1.1932761669158936, 3.9024429321289062, -3.467029571533203, -2.966586112976074, -1.409710168838501, 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{"paper_id": "tan2021distributed", "title": "Distributed Group Coordination of Multiagent Systems in Cloud Computing Systems Using a Model-Free Adaptive Predictive Control Strategy", "abstract": "A novel networked model-free adaptive predictive control (NMFAPC) strategy combining networked predictive control theory with model- free adaptive control method is proposed, which provides a solution for the coordination of large-scale nonlinear MASs.", "link": "dblp.org/rec/journals/tnn/TanWWHM22", "authors": "Haoran Tan and Yaonan Wang and Min Wu and Zhiwu Huang and Zhiqiang Miao", "year": "2021", "journal": "IEEE Transactions on Neural Networks and Learning Systems", "embeddings": [-4.192849159240723, 0.01308586448431015, -0.4561523497104645, 8.06423282623291, -3.225717544555664, -2.7327802181243896, 4.7633771896362305, -1.7946324348449707, 2.9378795623779297, -2.673668622970581, -0.2401585876941681, 0.6849410533905029, -0.35225895047187805, -4.572895050048828, -2.1441993713378906, 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-1.038351058959961, -1.4563316106796265, 2.039022445678711, 3.4394893646240234, 5.774673938751221, 0.7964415550231934, 2.8353488445281982, -0.6053528189659119, 1.7089821100234985, -0.6026135683059692, -1.537221908569336, -0.8782711029052734, 0.7121456265449524, 1.5441838502883911, 1.0651534795761108, -4.804793357849121]}, "liu2020coordinated": {"paper_id": "liu2020coordinated", "title": "Coordinated Control of Networked Multiagent Systems via Distributed Cloud Computing Using Multistep State Predictors", "abstract": "A distributed cloud predictive control scheme is proposed to achieve desired coordination control performance and compensate actively for communication delays between the cloud computing nodes and between the agents.", "link": "dblp.org/rec/journals/tcyb/Liu22", "authors": "Guoping Liu", "year": "2020", "journal": "IEEE Transactions on Cybernetics", "embeddings": [-4.18703556060791, -2.0945489406585693, 1.6544747352600098, 6.96705436706543, -3.516329765319824, 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and its applications.", "link": "", "authors": "Guo-Ping Liu", "year": "2017", "journal": "IEEE Transactions on Cybernetics", "embeddings": [-2.0712497234344482, -3.532973527908325, 1.449630856513977, 8.056333541870117, -0.5618331432342529, -2.902963876724243, 8.187276840209961, -2.628201723098755, 4.685553073883057, -3.5649020671844482, 0.611101508140564, -1.539169192314148, 0.31987982988357544, -5.021033763885498, -2.126779556274414, 0.05973729491233826, -1.266916036605835, -2.2804839611053467, -1.5082460641860962, 0.19031864404678345, -4.657916069030762, 4.8723063468933105, -6.102460861206055, -3.4363913536071777, -0.2828998863697052, -2.149259090423584, 4.324151992797852, -1.0534332990646362, 7.667233467102051, -1.950451135635376, 0.18404152989387512, 0.879518449306488, 3.513073444366455, 0.26759594678878784, 7.102249622344971, -3.5607850551605225, -0.5099223256111145, 0.5304573774337769, -1.1482250690460205, 2.4204277992248535, -0.42782628536224365, 1.9097590446472168, 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Edge Computing", "abstract": "A mist\u2013fog\u2013cloud predictive control scheme is proposed for the coordinated control of complex large-scale networked multiagent systems by making use of the advantages of cloud edge computing.", "link": "dblp.org/rec/journals/tcns/Liu22", "authors": "Guo-Ping Liu", "year": "2022", "journal": "IEEE Transactions on Control of Network Systems", "embeddings": [-4.023176670074463, -2.7796356678009033, 0.3442307114601135, 7.479586601257324, -2.709865093231201, -3.347287654876709, 6.709062099456787, -5.283897399902344, 4.315578460693359, -2.3736355304718018, 1.5759680271148682, -0.12981680035591125, -1.6439142227172852, -6.4574360847473145, -3.322911262512207, -0.27423301339149475, -2.359466791152954, 0.377399206161499, -0.8494585156440735, 0.4454392194747925, -4.529595375061035, 3.1965386867523193, -4.042797088623047, -3.936746120452881, -0.7121702432632446, -3.0599145889282227, 3.6314425468444824, -1.2955162525177002, 5.977658271789551, 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2.618385076522827, -2.141122341156006, -0.46912461519241333, -4.057877063751221]}, "yang2021predictive": {"paper_id": "yang2021predictive", "title": "Predictive Cloud Control for Networked Multiagent Systems With Quantized Signals Under DoS Attacks", "abstract": "A predictive cloud control scheme is investigated for a networked multiagent system (NMAS) with quantized signals under denial-of-service (DoS) attacks with effectiveness and computing superiority demonstrated by simulation results.", "link": "dblp.org/rec/journals/tsmc/YangJXZ21", "authors": "Hongjiu Yang and Shuang Ju and Yuanqing Xia and Jinhui Zhang", "year": "2021", "journal": "IEEE Transactions on Systems, Man, and Cybernetics: Systems", "embeddings": [0.960144579410553, -3.5281822681427, -0.904107391834259, 9.093992233276367, -1.0967097282409668, -3.5714027881622314, 7.64389705657959, -5.1418137550354, 3.165760040283203, -3.8230338096618652, -0.7133845686912537, 2.114508867263794, 2.030930995941162, -4.531224250793457, 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Ageed and Rowaida Khalil Ibrahim and M. A. 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output of the CBMF-MAS, a novel data-driven networked distributed predictive control method (DDNDPC) is presented, which is independent of system's structure model and only relies on system\u2019s input and output data.", "link": "dblp.org/rec/journals/tcas/TanMWWH20", "authors": "Haoran Tan and Zhiqiang Miao and Yaonan Wang and Min Wu and Zhiwu Huang", "year": "2020", "journal": "IEEE Transactions on Circuits and Systems Part 1: Regular Papers", "embeddings": [-2.658600330352783, -1.1749794483184814, -0.5903416872024536, 6.311332702636719, -1.8799128532409668, -1.1718332767486572, 4.009330749511719, -2.893092155456543, 2.6230456829071045, -2.271261215209961, -0.9850431680679321, 1.3276665210723877, 0.041420817375183105, -3.933192253112793, -2.7049758434295654, -1.2821625471115112, 1.4419009685516357, 2.403061628341675, 1.791151762008667, -2.319983959197998, -5.207597732543945, 4.684002876281738, -4.2972917556762695, -2.9938831329345703, -0.1639316976070404, -3.2476720809936523, 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-2.9262356758117676, 1.1120024919509888, -0.656742513179779, 0.40168067812919617, -4.253058433532715]}, "erg\u00fcn2020an": {"paper_id": "erg\u00fcn2020an", "title": "An application of crypto cloud computing in social networks by cooperative game theory", "abstract": "This paper mathematically associates Crypto Cloud Computing with Cooperative Game Theory in the presence of uncertainty, and suggests some interval solutions related with the model by proposing a novel elliptic curve public key encryption scheme over finite fields having the property of semantic security.", "link": "", "authors": "S. Erg\u00fcn and Baris B\u00fclent Kirlar and S. Z. A. G\u00f6k and G. Weber", "year": "2020", "journal": "Journal of Industrial and Management Optimization", "embeddings": [-4.402881145477295, -1.9818806648254395, -0.8504073619842529, 3.0959556102752686, 0.39830562472343445, -0.15387512743473053, 3.3093061447143555, -4.309566974639893, -2.076570987701416, -1.8399639129638672, -0.47664690017700195, -1.2745051383972168, 4.3394880294799805, -7.787410736083984, -3.5871071815490723, -1.0193426609039307, -3.2932629585266113, -8.540863037109375, -1.2682455778121948, -0.2143217921257019, -0.6859244108200073, 0.8774148225784302, -4.005351543426514, 0.2621229887008667, 1.459282398223877, -1.0239717960357666, 2.6971144676208496, -0.6588733196258545, 3.041623592376709, -3.483210802078247, 0.6583553552627563, -5.546092987060547, 5.058028697967529, 1.7297977209091187, 3.489072799682617, -4.223264694213867, -2.0710737705230713, 3.3476638793945312, -1.040514588356018, -0.0297679603099823, -1.1977121829986572, 3.4124951362609863, 0.225288525223732, -2.007606267929077, 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NG_TSRA is put forward that can improve the average power efficiency of the cloud computing system and proves the existence of Nash Equilibrium point of the game.", "link": "", "authors": "G. 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"dblp.org/rec/conf/icea/WangYZWGM21", "authors": "Maoli Wang and Kunlun Yang and Yining Zhao and Yalin Wang and Jinan Guo and Xu Ma", "year": "2021", "journal": "International Conference on Intelligent Computing and its Emerging Applications", "embeddings": [-5.293642997741699, -2.860386848449707, -3.50689697265625, 6.970163345336914, 0.4242681562900543, 1.0509876012802124, -0.14936327934265137, -7.725749969482422, -0.805915117263794, -3.5673727989196777, 1.3475818634033203, -0.002559065818786621, 4.218171119689941, -4.875056743621826, -2.4567337036132812, 0.4202255606651306, 0.25383925437927246, -1.6762490272521973, 2.8703651428222656, 0.9318475723266602, -3.096736431121826, 1.9467130899429321, -2.6088809967041016, 0.22070366144180298, 1.6190580129623413, -2.363712787628174, 1.1489152908325195, 2.3742921352386475, -1.018194556236267, -7.124443531036377, 0.35233110189437866, -6.094533443450928, 5.733118534088135, 0.2584732174873352, 5.830473899841309, -6.554406642913818, 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GAME THEORY", "abstract": "This thesis forms the optimal coalition formation in federated clouds as an integer linear programming problem under the cloud service brokerage model proposed by Mashayekhy et al and proposes a fast polynomial time greedy algorithm to find a near optimal coalition.", "link": "", "authors": "Y. Khandelwal and Suresh Purini and Toni Papa", "year": "2019", "journal": "arXiv preprint", "embeddings": [-5.843333721160889, -0.6745094060897827, -1.74099862575531, 3.8772132396698, -2.9142792224884033, 0.7307614088058472, 1.3321653604507446, -6.570093154907227, -0.3135283887386322, -3.980595827102661, 0.5090118646621704, 2.189751625061035, 2.5415821075439453, -6.493499755859375, -5.739894866943359, 1.9417858123779297, -2.063091278076172, -4.4994730949401855, -0.21942183375358582, 0.34069767594337463, -3.728504180908203, 7.826712608337402, -2.653656482696533, -1.9900089502334595, 2.5043277740478516, -0.7224841117858887, 3.566709280014038, -1.6475310325622559, 0.0785873681306839, -3.2270846366882324, 0.8233904838562012, -5.643494606018066, 8.194647789001465, 2.3959479331970215, 3.611599922180176, -7.193587303161621, -3.950169563293457, 3.885162830352783, -0.9804934859275818, 2.786454677581787, 0.6554436087608337, -0.8194102644920349, 0.19366244971752167, -3.0689635276794434, 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the mutual benefits of local and global MCC providers\u2019 interactions, and effectively shares the distributed cloud resources.", "link": "dblp.org/rec/journals/access/Kim21i", "authors": "Sungwook Kim", "year": "2021", "journal": "IEEE Access", "embeddings": [-5.966705322265625, -6.033904075622559, -4.850478172302246, 7.465538024902344, -2.035520076751709, 0.6090630292892456, 3.286806106567383, -5.049037933349609, -1.2176587581634521, -3.4294378757476807, -0.6817184686660767, 2.159575939178467, 2.339108943939209, -5.059757232666016, -2.801900863647461, -0.8414915800094604, -1.8588600158691406, -2.612154722213745, 2.6024112701416016, 0.2766922414302826, -4.131624221801758, 3.8808681964874268, -1.4010087251663208, 0.13634175062179565, 0.2994652986526489, -2.6736979484558105, 2.932727575302124, -0.16978788375854492, 1.8185482025146484, -7.127765655517578, -1.5039000511169434, -3.5884885787963867, 5.630244731903076, 4.404642105102539, 3.718794822692871, -5.278685569763184, 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scheduling in cloud computing", "abstract": "New job scheduling technique is proposed using the concepts of game theory and genetic algorithm to provide Pareto optimal solution using Non-dominated Sorting Genetic Algorithm II (NSGA II) and also concentrates on minimizing the deadline violation and makespan for the jobs submitted by the user.", "link": "", "authors": "Alaka Ananth and K. Chandrasekaran", "year": "2015", "journal": "International Conference on Computing, Networking and Communications", "embeddings": [-3.7519493103027344, -2.7394700050354004, -4.526966571807861, 4.067447662353516, -1.456402063369751, 1.99127197265625, 1.318333387374878, -5.404109954833984, -0.2370879054069519, -1.8887178897857666, -0.4383571147918701, 0.8387573957443237, 2.518300771713257, -4.697206974029541, -1.6227349042892456, 3.149470090866089, -0.6640954613685608, -1.2431747913360596, 1.1204490661621094, 2.689384937286377, -3.253249168395996, 5.779936790466309, -1.2008934020996094, -1.3376039266586304, 0.02146495133638382, -2.9545481204986572, 2.849497079849243, -0.9379469156265259, -2.5001490116119385, -5.026772975921631, -0.6960506439208984, -3.2538440227508545, 5.446823596954346, 2.9423351287841797, 5.591588497161865, -2.5137977600097656, -2.7476160526275635, 2.8418712615966797, 0.13428986072540283, 0.8388043642044067, 2.81954288482666, 1.6878573894500732, -0.5601547956466675, 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reshaped from being a passive virtual market to become an active platform for monetizing data and a novel game theoretical model is proposed, which consists of a mix of cooperative and competitive strategies.", "link": "dblp.org/rec/journals/tnsm/BatainehBMWRB22", "authors": "A. Bataineh and J. Bentahar and R. Mizouni and Omar Abdel Wahab and Gaith Rjoub and M. Barachi", "year": "2021", "journal": "IEEE Transactions on Network and Service Management", "embeddings": [-3.8809926509857178, -1.5915735960006714, -5.935375213623047, 6.485128402709961, -1.7476012706756592, 0.38703465461730957, 2.0126705169677734, -4.54549503326416, -1.5246831178665161, -4.144927978515625, -1.872089147567749, -0.03618793934583664, 6.2518696784973145, -5.866820812225342, -5.444998264312744, -3.3629376888275146, 2.6297621726989746, -5.327142715454102, 2.271773338317871, 2.1366918087005615, -4.49581241607666, 4.533591270446777, -2.9578075408935547, 2.5132577419281006, -1.6451880931854248, -1.4406017065048218, 2.716266393661499, -1.7147603034973145, 1.3342974185943604, -2.7757720947265625, -0.25545716285705566, -3.5483508110046387, 5.906162738800049, 4.9735188484191895, 5.346161842346191, -5.829823017120361, -5.60535192489624, 3.6242570877075195, -2.678790807723999, -0.12850739061832428, 1.2474764585494995, -2.7424447536468506, 1.6021970510482788, -3.0025181770324707, 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applications leveraging FL, called FedGame, and evaluates its accuracy against centralized ML/DL schemes while preserving the privacy of Industrial systems but also its efficiency in providing required MECs resources and, thus, dealing withIIoT attacks.", "link": "dblp.org/rec/journals/tii/HoudaBKKG22", "authors": "Zakaria Abou El Houda and B. Brik and A. Ksentini and L. Khoukhi and M. Guizani", "year": "2022", "journal": "IEEE Transactions on Industrial Informatics", "embeddings": [-4.741179466247559, -2.3197598457336426, -1.7560651302337646, 8.94639778137207, -0.3803142309188843, -2.599412441253662, 0.8937632441520691, -6.961338043212891, -1.7823985815048218, -3.484825611114502, -4.459061622619629, -0.6169326901435852, 5.127391815185547, -4.9674835205078125, -7.456143856048584, -1.2682889699935913, -1.941625952720642, -1.3580893278121948, 1.4509919881820679, 2.71833872795105, -5.232853889465332, 1.0987104177474976, -2.130547523498535, 0.9680470824241638, -1.7838281393051147, -0.8212224841117859, 2.1393773555755615, -1.78090500831604, -0.784319281578064, -0.6990689039230347, 4.991875648498535, -3.08463191986084, 5.349998950958252, -2.7138147354125977, 5.936236381530762, -6.371861457824707, -3.7569780349731445, 6.97880744934082, -2.9075870513916016, 2.8216800689697266, 2.016498565673828, -2.4309659004211426, -0.27789005637168884, -3.9737191200256348, 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namely, pricing or reputation and highlights open problems, such as the lack of proper models for dynamic and incomplete information scenarios.", "link": "", "authors": "Jos\u00e9 M. F. Moura and R. Marinheiro and J. Silva", "year": "2019", "journal": "Paving the Way for 5G Through the Convergence of Wireless Systems", "embeddings": [-4.921865463256836, 0.5420888662338257, -2.703772783279419, 7.242410659790039, -3.754373550415039, -1.2445933818817139, 1.1517333984375, -3.839989185333252, 0.041396476328372955, -3.994119167327881, -1.964292287826538, -1.1063772439956665, 1.3889036178588867, -6.585897445678711, -2.983828544616699, -0.8222798109054565, -0.14708685874938965, -2.048430919647217, 0.9915589094161987, 2.901679754257202, -4.122984886169434, 4.129707336425781, -0.41672900319099426, -0.14675870537757874, 1.015825629234314, -1.680884838104248, 1.0740792751312256, -2.493161201477051, 1.2726610898971558, -2.009915828704834, -1.761309266090393, -1.1623694896697998, 4.352837085723877, 3.617358446121216, 7.257154941558838, -6.842004776000977, -7.217798709869385, 0.8859710693359375, 0.6835010647773743, 2.6872828006744385, 2.4863779544830322, -1.2751381397247314, 0.6444790363311768, 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that gives mutual advantages for devices and edge clouds while improving the system efficiency.", "link": "dblp.org/rec/journals/access/Kim22g", "authors": "Sungwook Kim", "year": "2022", "journal": "IEEE Access", "embeddings": [-3.6214444637298584, -1.4210584163665771, -5.03277587890625, 5.311922073364258, -0.6400173902511597, -0.49793219566345215, 0.894544243812561, -6.835265159606934, -2.076960802078247, -5.055606842041016, -0.9587500691413879, 0.11005425453186035, 2.9928395748138428, -5.71112585067749, -1.1470627784729004, 1.171738624572754, -2.2802987098693848, 1.212127923965454, 1.7846653461456299, 2.7258152961730957, -5.0557098388671875, 4.133924961090088, -2.5020573139190674, -1.1385531425476074, 1.6288483142852783, -3.2234790325164795, 0.7552354335784912, -0.06745022535324097, -2.7888095378875732, -5.975033760070801, -1.4215638637542725, -4.8965744972229, 5.916186809539795, 1.6408519744873047, 6.977091312408447, -5.180334091186523, -3.522718906402588, 2.9869823455810547, 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"abstract": "A distributed mechanism to analyze the interaction between OSPs and IoT MDs in the MEC enabled edge-cloud system by appling multi-leader multi-follower two-tier Stackelberg game theory and proposes two distributed algorithms, namely iterative proximal offloading algorithm (IPOA) and iterative Stackellberg game pricing algorithm (ISPA).", "link": "dblp.org/rec/journals/corr/abs-2101-05628", "authors": "Yi Su and Wenhao Fan and Yuan\u2019an Liu and Fan Wu", "year": "2021", "journal": "arXiv.org", "embeddings": [-3.807891368865967, 0.22437253594398499, -4.5357489585876465, 6.933844566345215, -0.9830019474029541, 1.073875069618225, -0.33488601446151733, -6.768191337585449, -0.7620142102241516, -2.314622402191162, 0.1049562320113182, -1.7499418258666992, 5.152442455291748, -6.231786251068115, -4.666244029998779, 0.8608881235122681, -2.6301352977752686, -1.027294635772705, 2.551218032836914, 0.061478808522224426, -2.862074851989746, 2.088608741760254, -0.5635348558425903, 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computation tasks and assure the maximum utility of each vehicle.", "link": "dblp.org/rec/conf/icufn/HossainKH21", "authors": "M. Hossain and Subina Khanal and E. Huh", "year": "2021", "journal": "International Conference on Ubiquitous and Future Networks", "embeddings": [-3.4382078647613525, -0.2990254759788513, -2.2111217975616455, 6.556478023529053, -1.3882801532745361, -0.8191036581993103, 3.1607539653778076, -6.703283309936523, -0.46741071343421936, -3.677229166030884, -1.6129534244537354, -0.06263846904039383, 1.3787899017333984, -4.908936500549316, -3.7757925987243652, 1.007710337638855, -1.4745978116989136, 0.2693434953689575, -0.7018272876739502, 2.2922208309173584, -3.7373571395874023, 2.8316080570220947, -1.7526507377624512, -1.9721734523773193, 1.711637020111084, -3.4856579303741455, 2.109231948852539, 1.738692045211792, 1.886147379875183, -4.14258337020874, 0.2292482554912567, -4.676174163818359, 6.640139579772949, 3.114144802093506, 2.850907802581787, -6.468512535095215, -4.277146339416504, 3.9990956783294678, -1.8854798078536987, -0.07001389563083649, 1.8094135522842407, 0.9398094415664673, 1.2530362606048584, -3.4295973777770996, 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DCR algorithm balances the distribution of traffic flow and in the same time makes the total travel time from origin to destination smaller.", "link": "dblp.org/rec/conf/itsc/LuL0C19", "authors": "Jiawei Lu and Jinglin Li and Quan Yuan and Bo Chen", "year": "2019", "journal": "International Conference on Intelligent Transportation Systems", "embeddings": [-4.514406204223633, -1.2968130111694336, -2.3445675373077393, 5.638697147369385, -3.490017890930176, -0.601073682308197, 2.4856598377227783, -5.990114688873291, 1.2024368047714233, -2.17563796043396, -0.9056369662284851, 1.8322558403015137, -0.14863137900829315, -3.7848386764526367, -3.0092852115631104, 3.9291276931762695, -1.0067682266235352, -0.3143746852874756, -0.6510031223297119, -1.1858537197113037, -3.4091105461120605, 8.690657615661621, -1.705702781677246, -3.970658779144287, 2.2874674797058105, -3.853219747543335, 4.140336036682129, -0.006668299436569214, -1.2297117710113525, -2.310617208480835, 1.880569577217102, 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Cooperative Multiagent System for Traffic Signal Control Using Game Theory and Reinforcement Learning", "abstract": "A two-mode agent architecture is proposed to effectively control the traffic congestion problem through independent and cooperative procedures and experimental results indicate that the proposed method can effectively reduce the average delay time in different traffic demand scenarios.", "link": "dblp.org/rec/journals/itsm/Abdoos21", "authors": "M. Abdoos", "year": "2020", "journal": "IEEE Intelligent Transportation Systems Magazine", "embeddings": [-3.1095705032348633, -0.16361355781555176, -1.7224799394607544, 5.428588390350342, -4.353546619415283, -2.032895088195801, 3.2849512100219727, -3.0038323402404785, 0.9975699782371521, -2.0686535835266113, -2.390784740447998, -1.1645622253417969, -0.8496701717376709, -6.4572319984436035, -1.7918219566345215, 0.7313315868377686, 0.7916958332061768, 0.7385571002960205, -0.6194287538528442, -2.37516188621521, -4.020561218261719, 6.2263994216918945, -3.3484725952148438, -6.587692737579346, 1.2506160736083984, -4.685103416442871, 5.8183135986328125, 0.5383355021476746, -1.5636030435562134, -1.327904462814331, -1.0860681533813477, -0.6244338154792786, 4.847623825073242, 1.3204634189605713, 5.103961944580078, -5.411860466003418, -4.654738426208496, 2.950732946395874, 0.5419846773147583, 2.307090997695923, -1.3026676177978516, -0.22982501983642578, -1.8504372835159302, -4.164573669433594, 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conventional neoclassical theory that permits agents to extend their spheres of interest beyond the self and enables them to condition their preferences on the preferences of other agents, thereby providing a mechanism with which to characterize complex social behavior.", "link": "dblp.org/rec/conf/icaart/Stirling11", "authors": "W. 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system situating on multiple-community networks reveals that the community structure plays a key role in the stability of the strategy evolution and certify that the payoff is crucial for individuals\u2019 dominating superiority over others in the system.", "link": "dblp.org/rec/journals/tsmc/ZhangZC20", "authors": "Jianlei Zhang and Yuying Zhu and Zengqiang Chen", "year": "2020", "journal": "IEEE Transactions on Systems, Man, and Cybernetics: Systems", "embeddings": [-5.220168590545654, -1.3233942985534668, -1.4330636262893677, 4.500442981719971, -1.7496049404144287, -1.899897813796997, 3.327151298522949, -2.8875160217285156, 2.348830223083496, -3.4900832176208496, -3.4841392040252686, -1.6931110620498657, -0.40513378381729126, -4.682873249053955, -3.6077804565429688, 0.2374752163887024, 0.933321475982666, -2.442878007888794, 1.395405650138855, -0.39683783054351807, -5.606953144073486, 4.3842291831970215, -5.050693988800049, -5.281604290008545, 3.0318727493286133, -1.0462958812713623, 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games are presented in the hope that simulating altruistic behavior in AI systems will make AI better suit real-world applications\u2014and thus may make the real world a better place.", "link": "dblp.org/rec/conf/aaai/Rothe21", "authors": "J. Rothe", "year": "2021", "journal": "AAAI Conference on Artificial Intelligence", "embeddings": [-4.902828216552734, 1.547410011291504, -1.1454410552978516, 2.005197048187256, 1.1967177391052246, 0.9690361022949219, -0.33900976181030273, -4.621706008911133, 1.9585686922073364, -1.555757761001587, -1.3060396909713745, -0.16719061136245728, 3.3573532104492188, -5.82142972946167, -3.9382314682006836, 1.5401173830032349, 3.597876787185669, -1.9883928298950195, -0.39798665046691895, -0.20348721742630005, -2.6829216480255127, 3.581719398498535, -3.174309253692627, -3.0659756660461426, 0.3802946209907532, -4.889299392700195, 3.721778631210327, -0.5047228932380676, 3.5587432384490967, 3.2474365234375, -0.9603332281112671, -4.514416694641113, 4.226845741271973, -5.131917953491211, 3.8209846019744873, -7.043453693389893, -0.7877190113067627, 0.5696730613708496, 0.6884599924087524, -0.271916925907135, -2.4330453872680664, 1.3191606998443604, 2.2661900520324707, -2.8268792629241943, 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cooperative multiplayer video game is compared with a system where its agents choose actions randomly, then the average score of the systems are compared.", "link": "", "authors": "Reinaldo Ignatius Wijaya and N. Maulidevi", "year": "2019", "journal": "2019 International Conference of Advanced Informatics: Concepts, Theory and Applications (ICAICTA)", "embeddings": [-3.7819905281066895, -2.890921115875244, -3.586869239807129, 3.7191784381866455, -0.7091872692108154, 0.30859678983688354, 2.492311954498291, -3.394369125366211, -1.2780102491378784, 0.3474634289741516, -4.573483467102051, 1.2133287191390991, 2.447216749191284, -2.5501010417938232, -0.5494434237480164, -0.8603858947753906, 3.0920543670654297, -2.511631965637207, 3.1481428146362305, -1.0261150598526, 0.8157278895378113, 2.422718048095703, -4.986085891723633, -0.04138469696044922, -1.3576791286468506, -2.5198395252227783, 1.6666080951690674, 7.333372116088867, -0.04612308740615845, 3.6224746704101562, 4.4068379402160645, -4.246232986450195, 4.587215900421143, -2.921098232269287, 6.65496301651001, -5.065649032592773, -3.105916976928711, 3.0386345386505127, -0.11572295427322388, 0.6368827223777771, -0.27630123496055603, 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presented controller, not only guarantees the multi-agent system is uniformly ultimately bounded (UUB), but also minimizes the cooperative performance index function.", "link": "", "authors": "Jiao Dai and Chunsheng Liu and Jingliang Sun", "year": "2018", "journal": "ACM Cloud and Autonomic Computing Conference", "embeddings": [-2.616438865661621, -0.5505003333091736, 0.691733717918396, 6.3403730392456055, -3.7693166732788086, -2.3098301887512207, 3.584256172180176, -6.721391201019287, 5.034749507904053, -3.568917989730835, 0.01184767484664917, -1.3348937034606934, -0.8379566669464111, -3.3566927909851074, -2.2542343139648438, 1.736329197883606, -2.1755363941192627, 1.4462214708328247, -0.15691708028316498, -0.2745830714702606, -2.8518569469451904, 9.844962120056152, -7.687531471252441, -3.550297737121582, -1.095073938369751, -4.065581321716309, 4.436648845672607, 1.8239282369613647, 3.9856629371643066, 0.44778555631637573, -0.6109170317649841, -0.01941549777984619, 2.814404010772705, 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"yazdanpanah2020transaction", "title": "Transaction Cost Allocation in Industrial Symbiosis: A Multiagent Systems Approach", "abstract": ". This paper discusses the dynamics of Transaction Cost (TC) in Industrial Symbiosis Institutions (ISI) and provides a fair and stable mechanism for TC allocation among the involved \ufb01rms in a given ISI. In principle, industrial symbiosis, as an implementation of the circular economy paradigm in the context of industrial relation, is a practice aiming at reducing the material/energy foot-print of the \ufb01rms. The well-engineered form of this practice is proved to decrease the transaction costs at a collective level. This can be achieved using information systems for identifying potential synergies, evaluating mutually bene\ufb01cial ones, implementing the contracts, and governing the behavior of the established relations. Then the question is: \u201c how to distribute the costs for maintaining such an information system in a fair and stable manner? \u201d We see such a cost as a collective transaction cost and employ an integrated method rooted in cooperative game theory and multiagent systems research to develop a fair and stable allocation mechanism for it. The contribution is twofold: in developing computational multiagent methods for capturing the dynamics of transaction costs in industrial symbiosis and in presenting a novel game-theoretic mechanism for its allocation in industrial symbiosis institutions.", "link": "", "authors": "V. Yazdanpanah and D. Yazan and W. Zijm", "year": "2020", "journal": "arXiv preprint", "embeddings": [-3.152085065841675, -2.042954206466675, -0.7748125195503235, 4.1531267166137695, -3.0253496170043945, 1.2997658252716064, 1.6568503379821777, -3.19748854637146, -0.5261977910995483, -1.2656360864639282, -1.2824511528015137, -0.08523057401180267, 0.4932270646095276, -5.4913835525512695, -2.423224925994873, 0.6856603026390076, 5.693781852722168, -4.009662628173828, -0.5850735306739807, 1.5153241157531738, -2.234758138656616, 5.427942752838135, -6.657863616943359, -2.4642207622528076, 0.7404124736785889, -2.409269094467163, 3.277029275894165, -3.877319097518921, 0.8558330535888672, -1.6325798034667969, -4.753708362579346, -4.354798793792725, 4.310990810394287, -0.06434783339500427, 0.6263411045074463, -7.512478351593018, -3.8345866203308105, 1.695444107055664, -0.1221114993095398, 2.0905568599700928, -1.0391185283660889, 1.1707274913787842, -0.7283325791358948, -4.217702388763428, -2.2435715198516846, 3.4792425632476807, 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themselves, enabling them to synchronize in order to achieve complex goals that require sequential executions.", "link": "dblp.org/rec/conf/irc/ParkPLHLAFKM18", "authors": "Sujin Park and Sang-Gyu Park and Hyeonggun Lee and Minji Hyun and Eunsuh Lee and Jeonghyeon Ahn and Lauren Featherstun and Yongho Kim and E. Matson", "year": "2018", "journal": "International Conference on Robotic Computing", "embeddings": [-2.8848278522491455, -2.828653335571289, 1.7078920602798462, 6.14243745803833, -1.6144137382507324, -2.3204996585845947, 1.7933698892593384, -2.8464412689208984, 1.0369200706481934, -1.520250916481018, -1.7830936908721924, 1.6795387268066406, -2.0108699798583984, -1.8657968044281006, -2.8904709815979004, 0.850222110748291, 2.5082273483276367, 1.682265043258667, 3.366884469985962, 0.09203571081161499, -1.4529228210449219, 6.7300615310668945, -2.986231803894043, -2.8209316730499268, 0.0736965537071228, -4.335224628448486, 4.695979118347168, 0.8337348103523254, 1.7508243322372437, 2.596987247467041, -0.7823737263679504, -2.451592445373535, 5.681465148925781, -4.014853000640869, 3.3483400344848633, -7.291433334350586, -1.6450364589691162, 1.7637815475463867, 0.6680843830108643, 2.689610719680786, 1.760670781135559, 1.7007637023925781, -0.11797541379928589, -5.930440902709961, 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waiting time utilizes multiagent-based deep reinforcement learning (DRL) for the MEC servers that interact with IoV and traffic lights to generate dynamic green waves at congested intersections.", "link": "dblp.org/rec/journals/tcss/WangHZZ22", "authors": "Tong Wang and Azhar Hussain and Lejun Zhang and Chenwei Zhao", "year": "2022", "journal": "IEEE Transactions on Computational Social Systems", "embeddings": [-2.5300583839416504, -2.3308634757995605, -3.171337604522705, 5.938615798950195, -1.7036654949188232, -0.6692125797271729, 5.113792896270752, -5.441929340362549, 2.0104048252105713, -3.1865100860595703, -0.5196863412857056, -0.6204438209533691, 0.5465265512466431, -5.957279682159424, -3.3120803833007812, 1.5516622066497803, -3.252108335494995, -1.2387683391571045, -0.7346407175064087, 1.934382438659668, -3.6840686798095703, 2.3590147495269775, 0.47187888622283936, -2.11651611328125, -0.4624037444591522, -3.919555187225342, 3.4432389736175537, 1.8561859130859375, 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Joshi and Tzvetan T. Drashansky and J. Rice and S. Weerawarana and E. Houstis", "year": "1995", "journal": "arXiv preprint", "embeddings": [-1.944961428642273, -3.474585771560669, 2.2022271156311035, 4.016899585723877, -1.3346468210220337, 1.2597756385803223, 3.185070753097534, -3.8360049724578857, -0.9487755298614502, -1.6921825408935547, -0.5538709163665771, 3.010622024536133, -1.4679887294769287, -3.6358425617218018, -1.1744035482406616, -1.3823641538619995, 3.659074068069458, 1.9114415645599365, 1.11178719997406, 0.9126957654953003, -0.21975716948509216, 5.238495826721191, -7.257821083068848, -1.4756598472595215, 0.5023307204246521, -2.569702386856079, 3.0581271648406982, 2.1560919284820557, 1.844850778579712, 0.9902295470237732, -1.1598141193389893, -2.4072861671447754, 5.396784782409668, -3.48037052154541, 6.955320835113525, -3.7563881874084473, -3.238179922103882, 1.2992035150527954, 2.1480326652526855, 1.1168302297592163, 1.0386801958084106, 0.6972098350524902, 1.0711899995803833, 0.7146525382995605, 0.6268699765205383, 2.2592639923095703, 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formally expresses them as Event Calculus (EC) theories.", "link": "dblp.org/rec/conf/acsos/ElakehalV21", "authors": "Emad Eldeen Elakehal and Joost Vennekens", "year": "2021", "journal": "2021 IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion (ACSOS-C)", "embeddings": [-3.488210678100586, -1.9178494215011597, 3.0175132751464844, 3.1019864082336426, -0.3221830129623413, -1.354090929031372, 0.36036667227745056, -0.3326563835144043, 1.0303258895874023, 0.4456179440021515, 2.702672004699707, 1.773712396621704, -2.6607134342193604, -3.4377810955047607, -2.6210012435913086, 0.845297634601593, 3.656628131866455, 0.007223933935165405, 1.2553138732910156, -0.20100733637809753, -0.3605671226978302, 6.633847236633301, -5.625594139099121, -1.848678708076477, 1.0907918214797974, -0.3947882056236267, 2.6657257080078125, -0.4678669571876526, -0.37262076139450073, 0.5883966684341431, -1.760015606880188, -2.3578269481658936, 4.672297477722168, 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"smarsly2012multiagent", "title": "Multiagent-Based Collaborative Framework for a Self-Managing Structural Health Monitoring System", "abstract": "The multiagent framework has been implemented and validated for the monitoring of a 500-kW wind turbine in Germany and shows the practicability, efficiency, fault tolerance, and robustness of the system for structural health monitoring applications.", "link": "dblp.org/rec/journals/jccee/SmarslyLH12", "authors": "K. 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Hartmann", "year": "2012", "journal": "Journal of computing in civil engineering", "embeddings": [-0.039768993854522705, -2.4734249114990234, 2.4995532035827637, 5.060538291931152, -2.3060195446014404, -1.5545638799667358, -1.5758754014968872, -1.8269680738449097, 1.2664365768432617, 0.8510735034942627, -3.072338104248047, 1.5566307306289673, -1.1190485954284668, -1.68472421169281, 0.3489200174808502, -0.9387539625167847, 4.087573051452637, 1.05681574344635, -1.1300983428955078, -0.48341161012649536, -1.9267317056655884, 1.7301758527755737, -2.587641716003418, -0.2555992901325226, 1.5134797096252441, -0.37311241030693054, 3.5613276958465576, -2.8847837448120117, -0.20295482873916626, -1.7364331483840942, -5.751331329345703, 1.0283721685409546, 2.579929828643799, -0.2595982849597931, 4.12563419342041, -3.0171542167663574, -4.042642116546631, 1.197954535484314, -1.4934055805206299, 1.63887357711792, 3.672468662261963, 1.4904718399047852, -0.9150528311729431, -2.7753090858459473, 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through the tasks they carry out to fulfill objectives and goals is proposed.", "link": "", "authors": "Mar\u00eda Ang\u00e9lica Torres and L. G. Montan\u00e9 Jim\u00e9nez and M. T. CEPERO GARC\u00cdA", "year": "2021", "journal": "DYNA NEW TECHNOLOGIES", "embeddings": [-4.068417072296143, -4.514904499053955, -0.18576589226722717, 3.3912606239318848, -1.7058098316192627, -0.5652068257331848, 1.040602445602417, -0.7780569791793823, -0.46960562467575073, -3.261376142501831, -0.23640534281730652, 1.900840163230896, -3.7596938610076904, -3.703855276107788, 0.17655807733535767, 1.0911020040512085, 3.458988666534424, 4.755237579345703, 1.9969050884246826, 0.94366055727005, -1.1496118307113647, 8.257036209106445, -2.9680826663970947, -0.09734457731246948, 1.794565200805664, -2.3046460151672363, 2.0919952392578125, -0.4193826913833618, 3.0680975914001465, 3.8493704795837402, -2.620654582977295, 0.40367957949638367, 4.4669623374938965, -4.166075706481934, 5.980120658874512, -3.6499240398406982, -4.675272464752197, 0.6040130853652954, 2.0685911178588867, 1.5543439388275146, 0.1408793330192566, 4.370523452758789, -0.7410571575164795, -2.723778486251831, 3.6483068466186523, 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accommodation of existing simulators, satisfactory performance for adopting grid computing technique, and systematic data analysis tool.", "link": "dblp.org/rec/conf/cts/TakashinaBDZTSW05", "authors": "T. Takashina and Z. Bi and A. Damba and Guilan Zhi and Kazuhide Tanaka and Hiroki Sayama and Shigeyoshi Watanabe", "year": "2005", "journal": "Proceedings of the 2005 International Symposium on Collaborative Technologies and Systems, 2005.", "embeddings": [-3.80277419090271, -1.6876202821731567, -1.9193428754806519, 2.6642138957977295, -1.4581772089004517, -1.32474684715271, 2.8305928707122803, -1.513899564743042, -0.14594298601150513, -0.7220354676246643, -1.7390251159667969, -0.21433639526367188, 2.0302295684814453, -3.9464049339294434, 0.3016032576560974, 1.1017358303070068, 3.8897526264190674, 2.2228806018829346, 2.2277355194091797, -1.4139481782913208, -3.2899580001831055, 5.295848846435547, -2.7351646423339844, -1.864084243774414, 2.322000026702881, -2.3600387573242188, 7.519299507141113, -0.6777265667915344, -0.6708698272705078, 2.1026108264923096, -1.2098467350006104, -0.09337684512138367, 5.146751880645752, -2.4476051330566406, 5.340124130249023, -7.086062431335449, -5.33524227142334, 0.7652461528778076, 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chain's cloud service based on cooperative game theory", "abstract": "The multiple agent parallel computing framework was established for port logistics chain cloud service, with the stable and efficient cloud genetic algorithm applied to the implementation process of logistics chain resource selection and collaborative computation.", "link": "", "authors": "Rongtao Ding", "year": "2015", "journal": "arXiv preprint", "embeddings": [-6.266066551208496, -3.8542513847351074, -2.780095100402832, 8.53173542022705, 1.0270429849624634, -0.7979161143302917, 1.9055886268615723, -4.673513412475586, -1.9832804203033447, -0.9511390924453735, 0.4876921474933624, -0.9886343479156494, 3.0500216484069824, -6.2317585945129395, -2.5296685695648193, 3.2883658409118652, -1.8313877582550049, -5.630866050720215, -0.09643623232841492, -2.9081132411956787, -2.9354519844055176, 8.371999740600586, 0.3853159546852112, -2.073072910308838, 2.0396034717559814, -1.3035411834716797, 4.922258377075195, 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-1.0123541355133057, -0.5938475131988525]}, "duan2022evolutionary": {"paper_id": "duan2022evolutionary", "title": "Evolutionary Game Analysis of Industry-University-Research Cooperative Innovation in Digital Media Enterprise Cluster Based on GS Algorithm", "abstract": "In order to study all the advantages and disadvantages of digital media enterprises, technological innovation can only be completed through cooperation. A kind of industry-university-research cooperative innovation evolutionary game method based on GS algorithm is proposed for digital media enterprise clusters. This method analyzes the evolutionary game theory of innovation and puts forward the evolutionary stability strategy of cooperative innovation between enterprises and research institutions. The results show that decreasing V is beneficial for the evolutionary game to approach the equilibrium point (1,1); that is, the greater the cost of independent innovation is compared with collaborative innovation, the stronger the willingness of both sides of the game to collaborative innovation. Enterprises and scientific research institutions are two different subjects with different interests. If they want to complete innovation cooperation, they need to formulate a perfect set of rules so that both sides of the game can carry out cooperative innovation according to the principles, so as to achieve the goal of cooperation.", "link": "", "authors": "Xuan Duan and Pengfei Sun and Xu Wang and Bisheng Zhan", "year": "2022", "journal": "Wireless Communications and Mobile Computing", "embeddings": [-3.4752519130706787, -1.6868923902511597, -4.596886157989502, 4.4299187660217285, -0.39163804054260254, 1.040606141090393, -0.015393468551337719, -7.324793338775635, -1.1652082204818726, -3.896646738052368, -3.0956413745880127, -5.581536769866943, 4.655958652496338, -4.795237064361572, -1.2684943675994873, 0.6156325340270996, 3.2464590072631836, -6.368957996368408, 0.9976125359535217, -3.2012104988098145, -6.578047752380371, 3.1643617153167725, -0.707616925239563, -4.703770637512207, 3.4664926528930664, -2.288285493850708, 7.305434226989746, 2.1536171436309814, -1.374091386795044, 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0.3690266013145447]}, "luo2020incentive": {"paper_id": "luo2020incentive", "title": "Incentive-Aware Micro Computing Cluster Formation for Cooperative Fog Computing", "abstract": "To efficiently achieve mutually beneficial task execution, the proposed mechanism groups the devices into multiple micro computing clusters (MCCs) that can exchange mutually beneficial actions by helping to compute or transmit tasks, making all of their performances no worse than local execution or execution in the fog server.", "link": "dblp.org/rec/journals/twc/LuoCZCW20", "authors": "Siqi Luo and Xu Chen and Zhi Zhou and Xiang Chen and Weigang Wu", "year": "2020", "journal": "IEEE Transactions on Wireless Communications", "embeddings": [-2.968860626220703, -2.9118666648864746, -2.9371931552886963, 4.7268877029418945, 0.728036642074585, -0.266201376914978, 4.955689907073975, -5.402888298034668, -1.1682054996490479, -5.329833984375, -0.27339398860931396, 0.5644984245300293, 2.5836894512176514, 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Hern\u00e1ndez and J. Recasens", "year": "2005", "journal": "arXiv preprint", "embeddings": [-0.8325523734092712, 1.9195971488952637, 2.1362619400024414, 0.4211057424545288, -0.8723796010017395, -1.5361948013305664, -0.8672248125076294, -4.578985214233398, 0.22268730401992798, -4.030876636505127, -1.8723803758621216, -1.3831857442855835, 1.986269235610962, -4.09940242767334, -2.316155433654785, 3.370093584060669, -1.885918378829956, -4.053602695465088, 1.3725812435150146, 1.5220351219177246, -2.2358627319335938, 3.8071935176849365, -5.216569900512695, -1.43714439868927, 2.7650609016418457, -2.209714651107788, 4.081227779388428, 0.3796560764312744, 2.773627758026123, 0.6647880673408508, -0.29723963141441345, -1.6526238918304443, 5.081461429595947, -0.9375194311141968, 0.9008277654647827, -6.59671688079834, -6.155274391174316, 2.623260021209717, 3.534487009048462, 2.2295122146606445, -5.350904941558838, 3.398639678955078, 0.8303366899490356, -6.042133808135986, -1.5199609994888306, 1.9922258853912354, 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charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. diff --git a/Playing_Atari_with_Deep_Reinforcement_Learning.pdf b/Playing_Atari_with_Deep_Reinforcement_Learning.pdf new file mode 100644 index 0000000000000000000000000000000000000000..5e2804a070620e110645d69518e47d8b6132529b Binary files /dev/null and b/Playing_Atari_with_Deep_Reinforcement_Learning.pdf differ diff --git a/README-en.md b/README-en.md new file mode 100644 index 0000000000000000000000000000000000000000..a80c6063c0896b0f9430524caedfa36cb60c99ba --- /dev/null +++ b/README-en.md @@ -0,0 +1,43 @@ +# Auto-Draft: Literatures Summarization Assistant + +This project aims to automatically summarize a field of research. + +***Features***: +* Automatically search related papers. +* Every claim has an appropriate citation. +* Output LaTeX template. + +This script requires GPT-4 access. One round of generation will take around 10 minutes and 15,000 tokens (0.5 to 0.8 US dollars). + +# Demo + +The following link provides a free demo of basic functions. +If you need more customized features, please refer to *Usage* for local deployment and modification. + +https://huggingface.co/spaces/auto-academic/auto-draft + +# Usage +1. Clone this repo： +```angular2html +git clone https://github.com/CCCBora/auto-draft +``` +2. Install dependencies: +```angular2html +pip install -r requirements.txt +``` +3. Set the `OPENAI_API_KEY` in the environment variables. +4. Edit `auto_backgrounds.py` to customize the topic you want to explore, and then run +```angular2html +python auto_backgrounds.py +``` + +# Example Outputs +The `outputs` folder contains some original outputs for given inputs. +They can be directly compiled using Overleaf. + +Page 1 | Page 2 +:-------------------------:|:-------------------------: +![](assets/page1.png "Page-1") | ![](assets/page2.png "Page-2") + + + diff --git a/README.md b/README.md new file mode 100644 index 0000000000000000000000000000000000000000..4f0aef55fefa0b2a93e5ddc6a1916b9dae885f66 --- /dev/null +++ b/README.md @@ -0,0 +1,51 @@ +--- +sdk: gradio +app_file: app.py +license: mit +title: 'Auto-Draft: 文献整ç†è¾…助工具' +colorTo: indigo +python_version: 3.10.10 +--- + + +# Auto-Draft: 文献整ç†è¾…助工具 + +这个项目旨在辅助AI领域学术论文的文献整ç†ã€‚æ供如下功能： +* 主题归纳： 自动æœç´¢ç›¸å…³æ–‡çŒ®ï¼Œæ€»ç»“相关工作。 +* 真实引用：所有引用的文献都有对应原文，é¿å…AI胡说八é“。 +* 生æˆLaTeX模æ¿ï¼š 输出结果一键编译。 + +è¿è¡Œè¿‡ç¨‹éœ€è¦èƒ½ä½¿ç”¨GPT-4çš„API Key. 生æˆä¸€ç¯‡è®ºæ–‡éœ€è¦15000 Tokens(大约0.5到0.8美元). 总共过程需è¦å¤§çº¦å分钟. + +# ä½“éªŒåœ°å€ +以下链接æ供简å•åŠŸèƒ½çš„å…费体验. 如果需è¦æ›´å®šåˆ¶åŒ–的功能, 请å‚ç…§*使用方法*进行本地部署和自行修改. + +https://huggingface.co/spaces/auto-academic/auto-draft + +# 使用方法 +1. 克隆此仓库： +```angular2html +git clone https://github.com/CCCBora/auto-draft +``` +2. 安装ä¾èµ–： +```angular2html +pip install -r requirements.txt +``` +3. 在环境å˜é‡ä¸­è®¾å®šOPENAI_API_KEY。 +4. 编辑`auto_backgrounds.py`以自定义想è¦æŽ¢ç´¢çš„主题和æ述，然åŽè¿è¡Œ +```angular2html +python auto_backgrounds.py +``` + +# 示例 +`outputs` 文件夹中æ供了部分输入的原始输出. ç»ç”±Overleaf直接编译得到. 也å¯ä»¥æŸ¥çœ‹æœ¬ç›®å½•ä¸‹çš„sample-output.pdf. + +Page 1 | Page 2 +:-------------------------:|:-------------------------: +![](assets/page1.png "Page-1") | ![](assets/page2.png "Page-2") + +# License +This project is licensed under the MIT License. +Some parts of the code are under different licenses, as listed below: + +* `latex-flatten.py`: Licensed under the Unlicense. Original source: [rekka/latex-flatten](https://github.com/rekka/latex-flatten). diff --git a/__pycache__/auto_backgrounds.cpython-310.pyc b/__pycache__/auto_backgrounds.cpython-310.pyc new file mode 100644 index 0000000000000000000000000000000000000000..f1a4deec13d131e837d94d5b3bd19053df7709a1 Binary files /dev/null and b/__pycache__/auto_backgrounds.cpython-310.pyc differ diff --git a/__pycache__/auto_draft.cpython-310.pyc b/__pycache__/auto_draft.cpython-310.pyc new file mode 100644 index 0000000000000000000000000000000000000000..18edf19244141fede7ac9cf84d0dab4f7141694a Binary files /dev/null and b/__pycache__/auto_draft.cpython-310.pyc differ diff --git a/__pycache__/references_generator.cpython-310.pyc b/__pycache__/references_generator.cpython-310.pyc new file mode 100644 index 0000000000000000000000000000000000000000..2548bba972cd73f4a96ac5cfe88dd820c05c4cdb Binary files /dev/null and b/__pycache__/references_generator.cpython-310.pyc differ diff --git a/__pycache__/section_generator.cpython-310.pyc b/__pycache__/section_generator.cpython-310.pyc new file mode 100644 index 0000000000000000000000000000000000000000..efc4b5543b24ae01a7737159e4f0e7f8b07bdcf2 Binary files /dev/null and b/__pycache__/section_generator.cpython-310.pyc differ diff --git a/a81d76e64c3d70f77bc42dbced229d1d.zip b/a81d76e64c3d70f77bc42dbced229d1d.zip new file mode 100644 index 0000000000000000000000000000000000000000..ae15687d0aef3fb3632f8279a7ae43a0fad3b9df Binary files /dev/null and b/a81d76e64c3d70f77bc42dbced229d1d.zip differ diff --git a/api_wrapper.py b/api_wrapper.py new file mode 100644 index 0000000000000000000000000000000000000000..975e963545296d64edd21c78d073e552f8240a00 --- /dev/null +++ b/api_wrapper.py @@ -0,0 +1,29 @@ +''' +This script is used to wrap all generation methods together. + +todo: + A worker keeps running on the server. Monitor the Amazon SQS. Once receive a new message, do the following: + Download the corresponding configuration files on S3. + Change Task status from Pending to Running. + Call `generator_wrapper` and wait for the outputs. + If `generator_wrapper` returns results: + evaluate the results; compile it; upload results to S3 ... Change Task status from Running to Completed. + If anything goes wrong, raise Error. + If `generator_wrapper` returns nothing or Timeout, or raise any error: + Change Task status from Running to Failed. +''' + +from auto_backgrounds import generate_draft +import json + + +GENERATOR_MAPPING = {"draft": generate_draft} + +def generator_wrapper(path_to_config_json): + # Read configuration file and call corresponding function + with open(path_to_config_json, "r", encoding='utf-8') as f: + config = json.load(f) + + generator = GENERATOR_MAPPING.get(config["generator"]) + if generator is None: + pass \ No newline at end of file diff --git a/app.py b/app.py new file mode 100644 index 0000000000000000000000000000000000000000..f067b145bf8cf3e298c841eabef87cc2af21bfec --- /dev/null +++ b/app.py @@ -0,0 +1,275 @@ +import gradio as gr +import os +import openai +from auto_backgrounds import generate_backgrounds, generate_draft +from utils.file_operations import hash_name +from references_generator import generate_top_k_references + +# note: App白å±bug：å…许第三方cookie +# todo: +# 6. get logs when the procedure is not completed. * +# 7. 自己的文件库； 更多的prompts +# 8. Decide on how to generate the main part of a paper * (Langchain/AutoGPT +# 1. 把paper改æˆçº¯JSON? +# 2. 实现别的功能 +# 3. Check API Key GPT-4 Support. +# 8. Re-build some components using `langchain` +# - in `gpt_interation`, use LLM +# 5. 从æ供的bib文件中 找到citeå’Œcitedby的文章, 计算embeddings; 从整个paper list中 æ ¹æ®cosè·ç¦»è¿›è¡ŒæŽ’åº; 选å–max_refs的文章 +# future: +# 4. add auto_polishing function +# 12. Change link to more appealing color # after the website is built; +# 1. Check if there are any duplicated citations +# 2. Remove potential thebibliography and bibitem in .tex file + +####################################################################################################################### +# Check if openai and cloud storage available +####################################################################################################################### +openai_key = os.getenv("OPENAI_API_KEY") +access_key_id = os.getenv('AWS_ACCESS_KEY_ID') +secret_access_key = os.getenv('AWS_SECRET_ACCESS_KEY') +if access_key_id is None or secret_access_key is None: + print("Access keys are not provided. Outputs cannot be saved to AWS Cloud Storage.\n") + IS_CACHE_AVAILABLE = False +else: + IS_CACHE_AVAILABLE = True + +if openai_key is None: + print("OPENAI_API_KEY is not found in environment variables. The output may not be generated.\n") + IS_OPENAI_API_KEY_AVAILABLE = False +else: + openai.api_key = openai_key + try: + openai.Model.list() + IS_OPENAI_API_KEY_AVAILABLE = True + except Exception as e: + IS_OPENAI_API_KEY_AVAILABLE = False + + +def clear_inputs(*args): + return "", "" + +def clear_inputs_refs(*args): + return "", 5 + + +def wrapped_generator(paper_title, paper_description, openai_api_key=None, + paper_template="ICLR2022", tldr=True, max_num_refs=50, selected_sections=None, bib_refs=None, model="gpt-4", + cache_mode=IS_CACHE_AVAILABLE): + # if `cache_mode` is True, then follow the following steps: + # check if "title"+"description" have been generated before + # if so, download from the cloud storage, return it + # if not, generate the result. + if bib_refs is not None: + bib_refs = bib_refs.name + if openai_api_key is not None: + openai.api_key = openai_api_key + openai.Model.list() + + if cache_mode: + from utils.storage import list_all_files, download_file, upload_file + # check if "title"+"description" have been generated before + input_dict = {"title": paper_title, "description": paper_description, + "generator": "generate_draft"} + file_name = hash_name(input_dict) + ".zip" + file_list = list_all_files() + # print(f"{file_name} will be generated. Check the file list {file_list}") + if file_name in file_list: + # download from the cloud storage, return it + download_file(file_name) + return file_name + else: + # generate the result. + # output = fake_generate_backgrounds(title, description, openai_key) + output = generate_draft(paper_title, paper_description, template=paper_template, + tldr=tldr, max_num_refs=max_num_refs, + sections=selected_sections, bib_refs=bib_refs, model=model) + # output = generate_draft(paper_title, paper_description, template, "gpt-4") + upload_file(output) + return output + else: + # output = fake_generate_backgrounds(title, description, openai_key) + output = generate_draft(paper_title, paper_description, template=paper_template, + tldr=tldr, max_num_refs=max_num_refs, + sections=selected_sections, bib_refs=bib_refs, model=model) + return output + + +def wrapped_references_generator(paper_title, num_refs, openai_api_key=None): + if openai_api_key is not None: + openai.api_key = openai_api_key + openai.Model.list() + return generate_top_k_references(paper_title, top_k=num_refs) + + + +theme = gr.themes.Default(font=gr.themes.GoogleFont("Questrial")) +# .set( +# background_fill_primary='#E5E4E2', +# background_fill_secondary = '#F6F6F6', +# button_primary_background_fill="#281A39" +# ) + +ACADEMIC_PAPER = """## 一键生æˆè®ºæ–‡åˆç¨¿ + +1. 在Title文本框中输入想è¦ç”Ÿæˆçš„论文å称（比如Playing Atari with Deep Reinforcement Learning). +2. 点击Submit. 等待大概å分钟. +3. 在å³ä¾§ä¸‹è½½.zipæ ¼å¼çš„输出，在Overleaf上编译æµè§ˆ. +""" + + +REFERENCES = """## 一键æœç´¢ç›¸å…³è®ºæ–‡ +(此功能已ç»è¢«æ•´åˆè¿›ä¸€é”®ç”Ÿæˆè®ºæ–‡åˆç¨¿) +1. 在Title文本框中输入想è¦æœç´¢æ–‡çŒ®çš„论文（比如Playing Atari with Deep Reinforcement Learning). +2. 点击Submit. 等待大概å分钟. +3. 在å³ä¾§JSON处会显示相关文献. +""" + +REFERENCES_INSTRUCTION = """### References +这一行用于定义AI如何选å–å‚考文献. ç›®å‰æ˜¯ä¸¤ç§æ–¹å¼æ··åˆ: +1. GPT自动根æ®æ ‡é¢˜ç”Ÿæˆå…³é”®å­—，使用Semantic Scholaræœç´¢å¼•æ“Žæœç´¢æ–‡çŒ®ï¼Œåˆ©ç”¨Specter获å–Paper Embeddingæ¥è‡ªåŠ¨é€‰å–最相关的文献作为GPTçš„å‚考资料. +2. 用户上传bibtex文件，使用Google Scholaræœç´¢æ‘˜è¦ä½œä¸ºGPTçš„å‚考资料. +关于有希望利用本地文件æ¥ä¾›GPTå‚考的功能将在未æ¥å®žè£…. +""" + +DOMAIN_KNOWLEDGE_INSTRUCTION = """### Domain Knowledge +(暂未实装) +这一行用于定义AI的知识库. å°†æ供两ç§é€‰æ‹©: +1. å„个领域内由专家预先收集资料并构建的的FAISSå‘é‡æ•°æ®åº“. æ¯ä¸ªæ•°æ®åº“内包å«äº†æ•°ç™¾ä¸‡é¡µç»è¿‡åŒè¡Œè¯„议的论文和专业ç»å…¸ä¹¦ç±. +2. 自行构建的使用OpenAI text-embedding-ada-002模型创建的FAISSå‘é‡æ•°æ®åº“. +""" + +OTHERS_INSTRUCTION = """### Others + +""" + + +with gr.Blocks(theme=theme) as demo: + gr.Markdown(''' + # Auto-Draft: 文献整ç†è¾…助工具 + + 本Demoæ供对[Auto-Draft](https://github.com/CCCBora/auto-draft)çš„auto_draft功能的测试. + 通过输入想è¦ç”Ÿæˆçš„论文å称（比如Playing atari with deep reinforcement learning)，å³å¯ç”±AI辅助生æˆè®ºæ–‡æ¨¡æ¿. + + ***2023-05-17 Update***: 我的APIçš„ä½™é¢ç”¨å®Œäº†, 所以这个月ä¸å†èƒ½æä¾›GPT-4çš„API Key. 这里为大家æ供了一个ä½ç½®è¾“å…¥OpenAI API Key. åŒæ—¶ä¹Ÿæ供了GPT-3.5的兼容. 欢迎大家自行体验. + + 如果有更多想法和建议欢迎加入QQ群里交æµ, 如果我在Space里更新了Key我会第一时间通知大家. 群å·: ***249738228***. + ''') + + with gr.Row(): + with gr.Column(scale=2): + key = gr.Textbox(value=openai_key, lines=1, max_lines=1, label="OpenAI Key", + visible=not IS_OPENAI_API_KEY_AVAILABLE) + + # generator = gr.Dropdown(choices=["学术论文", "文献总结"], value="文献总结", + # label="Selection", info="ç›®å‰æ”¯æŒç”Ÿæˆ'学术论文'å’Œ'文献总结'.", interactive=True) + + # æ¯ä¸ªåŠŸèƒ½åšä¸€ä¸ªtab + with gr.Tab("学术论文"): + gr.Markdown(ACADEMIC_PAPER) + + title = gr.Textbox(value="Playing Atari with Deep Reinforcement Learning", lines=1, max_lines=1, + label="Title", info="论文标题") + + slider = gr.Slider(minimum=1, maximum=100, value=20, step=1, + interactive=True, visible=False, label="最大å‚考文献数目") + with gr.Accordion("高级设置", open=False): + with gr.Row(): + description_pp = gr.Textbox(lines=5, label="Description (Optional)", visible=True, + info="对希望生æˆçš„论文的一些æè¿°. 包括这篇论文的创新点, 主è¦è´¡çŒ®, ç­‰.") + with gr.Row(): + template = gr.Dropdown(label="Template", choices=["ICLR2022"], value="ICLR2022", + interactive=False, + info="生æˆè®ºæ–‡çš„å‚考模æ¿. (æš‚ä¸æ”¯æŒä¿®æ”¹)") + model_selection = gr.Dropdown(label="Model", choices=["gpt-4", "gpt-3.5-turbo"], + value="gpt-3.5-turbo", + interactive=True, + info="生æˆè®ºæ–‡ç”¨åˆ°çš„语言模型.") + sections = gr.CheckboxGroup( + choices=["introduction", "related works", "backgrounds", "methodology", "experiments", + "conclusion", "abstract"], + type="value", label="生æˆç« èŠ‚", interactive=True, + value=["introduction", "related works"]) + + with gr.Row(): + with gr.Column(scale=1): + gr.Markdown(REFERENCES_INSTRUCTION) + + with gr.Column(scale=2): + search_engine = gr.Dropdown(label="Search Engine", + choices=["ArXiv", "Semantic Scholar", "Google Scholar", "None"], + value="Semantic Scholar", + interactive=False, + visible=False, + info="用于决定GPT用什么æœç´¢å¼•æ“Žæ¥æœç´¢æ–‡çŒ®. (æš‚ä¸æ”¯æŒä¿®æ”¹)") + tldr_checkbox = gr.Checkbox(value=True, label="TLDR;", + info="选择此ç­è¡¨ç¤ºå°†ä½¿ç”¨Semantic Scholarçš„TLDR作为文献的总结.", + interactive=True) + gr.Markdown(''' + 上传.bib文件æä¾›AI需è¦å‚考的文献. + ''') + bibtex_file = gr.File(label="Upload .bib file", file_types=["text"], + interactive=True) + gr.Examples( + examples=["latex_templates/example_references.bib"], + inputs=bibtex_file + ) + + with gr.Row(): + with gr.Column(scale=1): + gr.Markdown(DOMAIN_KNOWLEDGE_INSTRUCTION) + + with gr.Column(scale=2): + domain_knowledge = gr.Dropdown(label="预载知识库", + choices=["(None)", "Machine Learning"], + value="(None)", + interactive=False, + info="使用预先构建的知识库. (暂未实装)") + local_domain_knowledge = gr.File(label="本地知识库 (暂未实装)", interactive=False) + with gr.Row(): + clear_button_pp = gr.Button("Clear") + submit_button_pp = gr.Button("Submit", variant="primary") + + with gr.Tab("文献æœç´¢"): + gr.Markdown(REFERENCES) + + title_refs = gr.Textbox(value="Playing Atari with Deep Reinforcement Learning", lines=1, max_lines=1, + label="Title", info="论文标题") + slider_refs = gr.Slider(minimum=1, maximum=100, value=5, step=1, + interactive=True, label="最相关的å‚考文献数目") + with gr.Row(): + clear_button_refs = gr.Button("Clear") + submit_button_refs = gr.Button("Submit", variant="primary") + + with gr.Tab("文献综述 (Coming soon!)"): + gr.Markdown(''' +

Coming soon!

+ ''') + with gr.Tab("Github文档 (Coming soon!)"): + gr.Markdown(''' +

Coming soon!

+ ''') + + with gr.Column(scale=1): + style_mapping = {True: "color:white;background-color:green", + False: "color:white;background-color:red"} # todo: to match website's style + availability_mapping = {True: "AVAILABLE", False: "NOT AVAILABLE"} + gr.Markdown(f'''## Huggingface Space Status + 当`OpenAI API`显示AVAILABLE的时候这个Spaceå¯ä»¥ç›´æŽ¥ä½¿ç”¨. + 当`OpenAI API`显示NOT AVAILABLE的时候这个Spaceå¯ä»¥é€šè¿‡åœ¨å·¦ä¾§è¾“å…¥OPENAI KEYæ¥ä½¿ç”¨. 需è¦æœ‰GPT-4çš„APIæƒé™. + 当`Cache`显示AVAILABLE的时候, 所有的输入和输出会被备份到我的云储存中. 显示NOT AVAILABLE的时候ä¸å½±å“实际使用. + `OpenAI API`: {availability_mapping[IS_OPENAI_API_KEY_AVAILABLE]}. `Cache`: {availability_mapping[IS_CACHE_AVAILABLE]}.''') + file_output = gr.File(label="Output") + json_output = gr.JSON(label="References") + + clear_button_pp.click(fn=clear_inputs, inputs=[title, description_pp], outputs=[title, description_pp]) + submit_button_pp.click(fn=wrapped_generator, + inputs=[title, description_pp, key, template, tldr_checkbox, slider, sections, bibtex_file, + model_selection], outputs=file_output) + + clear_button_refs.click(fn=clear_inputs_refs, inputs=[title_refs, slider_refs], outputs=[title_refs, slider_refs]) + submit_button_refs.click(fn=wrapped_references_generator, + inputs=[title_refs, slider_refs, key], outputs=json_output) + +demo.queue(concurrency_count=1, max_size=5, api_open=False) +demo.launch(share=True) diff --git a/assets/page1.png b/assets/page1.png new file mode 100644 index 0000000000000000000000000000000000000000..265a782341dd04ee52b007c2464035d4102115f7 Binary files /dev/null and b/assets/page1.png differ diff --git a/assets/page2.png b/assets/page2.png new file mode 100644 index 0000000000000000000000000000000000000000..b07364164f3eb929e3a3401f22b4ab0036d16619 Binary files /dev/null and b/assets/page2.png differ diff --git a/auto_backgrounds.py b/auto_backgrounds.py new file mode 100644 index 0000000000000000000000000000000000000000..f4840aa82800108db979cfd27517beeea22f881e --- /dev/null +++ b/auto_backgrounds.py @@ -0,0 +1,159 @@ +import os.path +from utils.references import References +from utils.file_operations import hash_name, make_archive, copy_templates +from utils.tex_processing import create_copies +from section_generator import section_generation_bg, keywords_generation, figures_generation, section_generation +from references_generator import generate_top_k_references +import logging +import time + + +TOTAL_TOKENS = 0 +TOTAL_PROMPTS_TOKENS = 0 +TOTAL_COMPLETION_TOKENS = 0 + + +def log_usage(usage, generating_target, print_out=True): + global TOTAL_TOKENS + global TOTAL_PROMPTS_TOKENS + global TOTAL_COMPLETION_TOKENS + + prompts_tokens = usage['prompt_tokens'] + completion_tokens = usage['completion_tokens'] + total_tokens = usage['total_tokens'] + + TOTAL_TOKENS += total_tokens + TOTAL_PROMPTS_TOKENS += prompts_tokens + TOTAL_COMPLETION_TOKENS += completion_tokens + + message = f"For generating {generating_target}, {total_tokens} tokens have been used ({prompts_tokens} for prompts; {completion_tokens} for completion). " \ + f"{TOTAL_TOKENS} tokens have been used in total.\n\n" + if print_out: + print(message) + logging.info(message) + +def _generation_setup(title, description="", template="ICLR2022", tldr=False, + max_kw_refs=10, max_num_refs=50, bib_refs=None, max_tokens=2048): + """ + This function handles the setup process for paper generation; it contains three folds + 1. Copy the template to the outputs folder. Create the log file `generation.log` + 2. Collect references based on the given `title` and `description` + 3. Generate the basic `paper` object (a dictionary) + + Parameters: + title (str): The title of the paper. + description (str, optional): A short description or abstract for the paper. Defaults to an empty string. + template (str, optional): The template to be used for paper generation. Defaults to "ICLR2022". + tldr (bool, optional): A flag indicating whether a TL;DR (Too Long; Didn't Read) summary should be generated for the collected papers. Defaults to False. + max_kw_refs (int, optional): The maximum number of references that can be associated with each keyword. Defaults to 10. + max_num_refs (int, optional): The maximum number of references that can be included in the paper. Defaults to 50. + bib_refs (list, optional): A list of pre-existing references in BibTeX format. Defaults to None. + + Returns: + tuple: A tuple containing the following elements: + - paper (dict): A dictionary containing the generated paper information. + - destination_folder (str): The path to the destination folder where the generation log is saved. + - all_paper_ids (list): A list of all paper IDs collected for the references. + """ + # print("Generation setup...") + paper = {} + paper_body = {} + + # Create a copy in the outputs folder. + bibtex_path, destination_folder = copy_templates(template, title) + logging.basicConfig(level=logging.INFO, filename=os.path.join(destination_folder, "generation.log") ) + + # Generate keywords and references + # print("Initialize the paper information ...") + input_dict = {"title": title, "description": description} + keywords, usage = keywords_generation(input_dict) + log_usage(usage, "keywords") + + # generate keywords dictionary + keywords = {keyword:max_kw_refs for keyword in keywords} + print(f"keywords: {keywords}\n\n") + + ref = References(title, bib_refs) + ref.collect_papers(keywords, tldr=tldr) + all_paper_ids = ref.to_bibtex(bibtex_path) + + print(f"The paper information has been initialized. References are saved to {bibtex_path}.") + + paper["title"] = title + paper["description"] = description + paper["references"] = ref.to_prompts(max_tokens=max_tokens) + paper["body"] = paper_body + paper["bibtex"] = bibtex_path + return paper, destination_folder, all_paper_ids #todo: use `all_paper_ids` to check if all citations are in this list + + + +def generate_backgrounds(title, description="", template="ICLR2022", model="gpt-4"): + # todo: to match the current generation setup + paper, destination_folder, _ = _generation_setup(title, description, template, model) + + for section in ["introduction", "related works", "backgrounds"]: + try: + usage = section_generation_bg(paper, section, destination_folder, model=model) + log_usage(usage, section) + except Exception as e: + message = f"Failed to generate {section}. {type(e).__name__} was raised: {e}" + print(message) + logging.info(message) + print(f"The paper '{title}' has been generated. Saved to {destination_folder}.") + + input_dict = {"title": title, "description": description, "generator": "generate_backgrounds"} + filename = hash_name(input_dict) + ".zip" + return make_archive(destination_folder, filename) + + + +def generate_draft(title, description="", template="ICLR2022", + tldr=True, max_kw_refs=10, max_num_refs=30, sections=None, bib_refs=None, model="gpt-4"): + # pre-processing `sections` parameter; + print("================PRE-PROCESSING================") + if sections is None: + sections = ["introduction", "related works", "backgrounds", "methodology", "experiments", "conclusion", "abstract"] + + # todo: add more parameters; select which section to generate; select maximum refs. + paper, destination_folder, _ = _generation_setup(title, description, template, tldr, max_kw_refs, max_num_refs, bib_refs) + + # main components + for section in sections: + print(f"================Generate {section}================") + max_attempts = 4 + attempts_count = 0 + while attempts_count < max_attempts: + try: + usage = section_generation(paper, section, destination_folder, model=model) + log_usage(usage, section) + break + except Exception as e: + message = f"Failed to generate {section}. {type(e).__name__} was raised: {e}\n" + print(message) + logging.info(message) + attempts_count += 1 + time.sleep(15) + + # post-processing + print("================POST-PROCESSING================") + create_copies(destination_folder) + input_dict = {"title": title, "description": description, "generator": "generate_draft"} + filename = hash_name(input_dict) + ".zip" + print("\nMission completed.\n") + return make_archive(destination_folder, filename) + + + + + + + +if __name__ == "__main__": + import openai + openai.api_key = os.getenv("OPENAI_API_KEY") + + title = "Using interpretable boosting algorithms for modeling environmental and agricultural data" + description = "" + output = generate_draft(title, description, tldr=True, max_kw_refs=10) + print(output) \ No newline at end of file diff --git a/auto_draft.py b/auto_draft.py new file mode 100644 index 0000000000000000000000000000000000000000..df2fabe5566c0cedd39b6282dd17e7efd2614ae3 --- /dev/null +++ b/auto_draft.py @@ -0,0 +1,145 @@ +# from utils.references import References +# from utils.prompts import generate_paper_prompts, generate_keywords_prompts, generate_experiments_prompts +# from utils.gpt_interaction import get_responses, extract_responses, extract_keywords, extract_json +# from utils.tex_processing import replace_title +# from utils.figures import generate_random_figures +# import datetime +# import shutil +# import time +# import logging +# import os +# +# TOTAL_TOKENS = 0 +# TOTAL_PROMPTS_TOKENS = 0 +# TOTAL_COMPLETION_TOKENS = 0 +# +# def make_archive(source, destination): +# base = os.path.basename(destination) +# name = base.split('.')[0] +# format = base.split('.')[1] +# archive_from = os.path.dirname(source) +# archive_to = os.path.basename(source.strip(os.sep)) +# shutil.make_archive(name, format, archive_from, archive_to) +# shutil.move('%s.%s'%(name,format), destination) +# return destination +# +# +# def log_usage(usage, generating_target, print_out=True): +# global TOTAL_TOKENS +# global TOTAL_PROMPTS_TOKENS +# global TOTAL_COMPLETION_TOKENS +# +# prompts_tokens = usage['prompt_tokens'] +# completion_tokens = usage['completion_tokens'] +# total_tokens = usage['total_tokens'] +# +# TOTAL_TOKENS += total_tokens +# TOTAL_PROMPTS_TOKENS += prompts_tokens +# TOTAL_COMPLETION_TOKENS += completion_tokens +# +# message = f"For generating {generating_target}, {total_tokens} tokens have been used ({prompts_tokens} for prompts; {completion_tokens} for completion). " \ +# f"{TOTAL_TOKENS} tokens have been used in total." +# if print_out: +# print(message) +# logging.info(message) +# +# def pipeline(paper, section, save_to_path, model): +# """ +# The main pipeline of generating a section. +# 1. Generate prompts. +# 2. Get responses from AI assistant. +# 3. Extract the section text. +# 4. Save the text to .tex file. +# :return usage +# """ +# print(f"Generating {section}...") +# prompts = generate_paper_prompts(paper, section) +# gpt_response, usage = get_responses(prompts, model) +# output = extract_responses(gpt_response) +# paper["body"][section] = output +# tex_file = save_to_path + f"{section}.tex" +# if section == "abstract": +# with open(tex_file, "w") as f: +# f.write(r"\begin{abstract}") +# with open(tex_file, "a") as f: +# f.write(output) +# with open(tex_file, "a") as f: +# f.write(r"\end{abstract}") +# else: +# with open(tex_file, "w") as f: +# f.write(f"\section{{{section}}}\n") +# with open(tex_file, "a") as f: +# f.write(output) +# time.sleep(5) +# print(f"{section} has been generated. Saved to {tex_file}.") +# return usage +# +# +# +# def generate_draft(title, description="", template="ICLR2022", model="gpt-4"): +# """ +# The main pipeline of generating a paper. +# 1. Copy everything to the output folder. +# 2. Create references. +# 3. Generate each section using `pipeline`. +# 4. Post-processing: check common errors, fill the title, ... +# """ +# paper = {} +# paper_body = {} +# +# # Create a copy in the outputs folder. +# # todo: use copy_templates function instead. +# now = datetime.datetime.now() +# target_name = now.strftime("outputs_%Y%m%d_%H%M%S") +# source_folder = f"latex_templates/{template}" +# destination_folder = f"outputs/{target_name}" +# shutil.copytree(source_folder, destination_folder) +# +# bibtex_path = destination_folder + "/ref.bib" +# save_to_path = destination_folder +"/" +# replace_title(save_to_path, title) +# logging.basicConfig( level=logging.INFO, filename=save_to_path+"generation.log") +# +# # Generate keywords and references +# print("Initialize the paper information ...") +# prompts = generate_keywords_prompts(title, description) +# gpt_response, usage = get_responses(prompts, model) +# keywords = extract_keywords(gpt_response) +# log_usage(usage, "keywords") +# ref = References(load_papers = "") #todo: allow users to upload bibfile. +# ref.collect_papers(keywords, method="arxiv") #todo: add more methods to find related papers +# all_paper_ids = ref.to_bibtex(bibtex_path) #todo: this will used to check if all citations are in this list +# +# print(f"The paper information has been initialized. References are saved to {bibtex_path}.") +# +# paper["title"] = title +# paper["description"] = description +# paper["references"] = ref.to_prompts() #todo: see if this prompts can be compressed. +# paper["body"] = paper_body +# paper["bibtex"] = bibtex_path +# +# print("Generating figures ...") +# prompts = generate_experiments_prompts(paper) +# gpt_response, usage = get_responses(prompts, model) +# list_of_methods = list(extract_json(gpt_response)) +# log_usage(usage, "figures") +# generate_random_figures(list_of_methods, save_to_path + "comparison.png") +# +# for section in ["introduction", "related works", "backgrounds", "methodology", "experiments", "conclusion", "abstract"]: +# try: +# usage = pipeline(paper, section, save_to_path, model=model) +# log_usage(usage, section) +# except Exception as e: +# print(f"Failed to generate {section} due to the error: {e}") +# print(f"The paper {title} has been generated. Saved to {save_to_path}.") +# return make_archive(destination_folder, "output.zip") +# +# if __name__ == "__main__": +# # title = "Training Adversarial Generative Neural Network with Adaptive Dropout Rate" +# title = "Playing Atari Game with Deep Reinforcement Learning" +# description = "" +# template = "ICLR2022" +# model = "gpt-4" +# # model = "gpt-3.5-turbo" +# +# generate_draft(title, description, template, model) diff --git a/e2c6f789-0515-11ee-ad29-085bd609d2a0.json b/e2c6f789-0515-11ee-ad29-085bd609d2a0.json new file mode 100644 index 0000000000000000000000000000000000000000..bbb50136c424d548a328a991bc518c10fbb7f88f --- /dev/null +++ b/e2c6f789-0515-11ee-ad29-085bd609d2a0.json @@ -0,0 +1 @@ +{"paszke2019pytorch": {"paper_id": "paszke2019pytorch", "title": "PyTorch: An Imperative Style, High-Performance Deep Learning Library", "abstract": "This paper details the principles that drove the implementation of PyTorch and how they are reflected in its architecture, and explains how the careful and pragmatic implementation of the key components of its runtime enables them to work together to achieve compelling performance.", "link": "dblp.org/rec/journals/corr/abs-1912-01703", "authors": "Adam Paszke and Sam Gross and Francisco Massa and Adam Lerer and James Bradbury and Gregory Chanan and Trevor Killeen and Zeming Lin and N. Gimelshein and L. Antiga and Alban Desmaison and Andreas K\u00f6pf and E. Yang and Zach DeVito and Martin Raison and A. Tejani and Sasank Chilamkurthy and Benoit Steiner and Lu Fang and Junjie Bai and Soumith Chintala", "year": "2019", "journal": "Neural Information Processing Systems", "embeddings": [-2.0042524337768555, -3.724529504776001, -0.6586412787437439, 2.7351582050323486, -1.1613483428955078, 3.2795023918151855, 1.6743825674057007, -1.1348843574523926, -1.5211703777313232, 1.748855471611023, -1.9655368328094482, 1.4608180522918701, 2.2022364139556885, 0.12803567945957184, -1.9455671310424805, -1.1167364120483398, -0.22569340467453003, 0.3278966546058655, 5.994208335876465, 4.826407432556152, 1.2469490766525269, -0.33040881156921387, -3.059044122695923, 4.162042140960693, -3.3616483211517334, -0.5787801742553711, 2.9157657623291016, -0.12785083055496216, -2.3617067337036133, 0.8776203989982605, 2.2817652225494385, -3.017336368560791, 3.9256532192230225, -4.264407157897949, 3.717944383621216, -3.574007034301758, -4.339020729064941, 7.3140950202941895, -5.474143028259277, -0.8086982369422913, 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"abstract": "This work studies the adversarial robustness of neural networks through the lens of robust optimization, and suggests the notion of security against a first-order adversary as a natural and broad security guarantee.", "link": "dblp.org/rec/conf/iclr/MadryMSTV18", "authors": "A. Madry and Aleksandar Makelov and Ludwig Schmidt and Dimitris Tsipras and Adrian Vladu", "year": "2017", "journal": "International Conference on Learning Representations", "embeddings": [0.037323907017707825, -1.628470540046692, 0.15469902753829956, 3.9273738861083984, -3.570990562438965, -3.175629138946533, 4.920684814453125, -1.449448823928833, -2.872925281524658, -0.8592929244041443, -2.7184269428253174, 5.639379978179932, 2.1084134578704834, -2.635369300842285, -4.564435005187988, -0.13109463453292847, -2.741763114929199, 1.5476703643798828, 1.084812879562378, 2.778709888458252, -2.143277645111084, 2.4123058319091797, -2.5870492458343506, -0.4967197775840759, -5.946282863616943, -3.013979196548462, 2.0305774211883545, -1.3545408248901367, -0.9628555178642273, 0.21794667840003967, -0.9883311986923218, -4.4802632331848145, 3.381453037261963, -2.0108957290649414, 1.5173377990722656, -4.414924621582031, 1.5949311256408691, 7.512564659118652, -6.529536247253418, -0.010784506797790527, 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dropout training in deep neural networks (NNs) as approximate Bayesian inference in deep Gaussian processes, which mitigates the problem of representing uncertainty in deep learning without sacrificing either computational complexity or test accuracy.", "link": "dblp.org/rec/journals/corr/GalG15", "authors": "Y. Gal and Zoubin Ghahramani", "year": "2015", "journal": "International Conference on Machine Learning", "embeddings": [-2.8253722190856934, 1.54095458984375, -0.018330443650484085, 2.682201862335205, -2.6561803817749023, 1.5002307891845703, 2.137376546859741, -1.135985016822815, -0.5761376619338989, 0.07662108540534973, -0.07667123526334763, 2.2768120765686035, -0.5698258876800537, -1.3171489238739014, -2.752934694290161, 3.507314443588257, -2.158604145050049, 3.3845746517181396, 3.459439277648926, 4.638561725616455, -4.019770622253418, 1.5354342460632324, -1.325339436531067, 0.2554664611816406, -2.2907583713531494, 0.9307647347450256, 2.2006795406341553, -2.846971273422241, -4.290031433105469, 2.5229620933532715, -4.234611988067627, -3.657386064529419, 4.891006946563721, -1.2478716373443604, 4.578426361083984, -0.9229859113693237, 0.1678154170513153, 5.282721519470215, -3.026660442352295, 1.0505480766296387, 1.4894309043884277, 2.0005440711975098, 2.000614643096924, 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network architecture inspired by Inception, where Inception modules have been replaced with depthwise separable convolutions, and shows that this architecture, dubbed Xception, slightly outperforms Inception V3 on the ImageNet dataset, and significantly outperforms it on a larger image classification dataset.", "link": "dblp.org/rec/journals/corr/Chollet16a", "authors": "Fran\u00e7ois Chollet", "year": "2016", "journal": "Computer Vision and Pattern Recognition", "embeddings": [-3.034724473953247, -3.335716962814331, 1.3077396154403687, 0.8205521106719971, 0.8761268258094788, 3.0871667861938477, 5.97266960144043, -3.591437816619873, -0.5757056474685669, -2.4915385246276855, 2.9338490962982178, 4.063416004180908, 0.2937496304512024, 1.742051362991333, -2.226600408554077, -1.4493743181228638, -1.2894431352615356, -0.950891375541687, 1.7324724197387695, 2.4764511585235596, 0.31014779210090637, 0.1744239628314972, -0.13588321208953857, 2.202181339263916, -2.713869333267212, 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Qi and Hao Su and Kaichun Mo and L. Guibas", "year": "2016", "journal": "Computer Vision and Pattern Recognition", "embeddings": [-3.331528663635254, -5.597233772277832, 0.11538910865783691, 2.1602425575256348, -1.4476182460784912, -1.470265507698059, 5.902702331542969, 1.169396162033081, 1.1811467409133911, 0.5998000502586365, -0.6732860803604126, 2.4276857376098633, 0.07427911460399628, 3.6766271591186523, -4.740270137786865, -0.27683424949645996, -1.0231194496154785, 3.352701425552368, 1.4785317182540894, 0.31587305665016174, 0.6053706407546997, 0.34480783343315125, -2.767334461212158, 0.1798175722360611, 1.714263677597046, -1.275045394897461, 0.5671573877334595, 2.5536932945251465, -1.7219152450561523, -4.044512748718262, 1.6424236297607422, -1.0048611164093018, 6.7587080001831055, -0.023182369768619537, 1.1443134546279907, 0.32616186141967773, 4.561947822570801, 2.081634998321533, -0.7922206521034241, -4.76909065246582, 4.6042351722717285, 2.0453412532806396, -0.7664517164230347, 0.9273681640625, 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based on deep machine learning had high sensitivity and specificity for detecting referable diabetic retinopathy and diabetic macular edema in retinal fundus photographs from adults with diabetes.", "link": "", "authors": "Varun Gulshan and L. Peng and Marc Coram and Martin C. Stumpe and Derek J. Wu and Arunachalam Narayanaswamy and Subhashini Venugopalan and Kasumi Widner and T. Madams and Jorge A Cuadros and R. Kim and R. Raman and Philip Nelson and J. Mega and D. Webster", "year": "2016", "journal": "Journal of the American Medical Association (JAMA)", "embeddings": [-1.4106111526489258, -4.7032084465026855, 0.6658257842063904, 3.043433666229248, -2.3476357460021973, 0.033837467432022095, 1.2072362899780273, 0.16655713319778442, -1.457754373550415, 1.913299798965454, -2.1827614307403564, 2.96201229095459, 1.364642858505249, 2.0192177295684814, -4.212244987487793, -1.9653387069702148, -2.362041473388672, 1.645559310913086, 1.772135615348816, 0.20801836252212524, -0.23211687803268433, -0.4084078371524811, 1.9119913578033447, 0.369056761264801, -4.021578788757324, 1.8554019927978516, -0.7737153172492981, 1.7365834712982178, -0.8028465509414673, 1.8555829524993896, -3.205305576324463, -3.3917651176452637, 5.650441646575928, 0.9954313635826111, 1.9828994274139404, 2.7752320766448975, 1.579880714416504, 3.368232488632202, -5.918262481689453, -1.4278554916381836, 2.832155466079712, -0.370293527841568, 4.280561923980713, 2.003380537033081, 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with stochastic gradient methods easily fit a random labeling of the training data, and confirm that simple depth two neural networks already have perfect finite sample expressivity.", "link": "dblp.org/rec/conf/iclr/ZhangBHRV17", "authors": "Chiyuan Zhang and Samy Bengio and Moritz Hardt and B. Recht and Oriol Vinyals", "year": "2016", "journal": "International Conference on Learning Representations", "embeddings": [-5.389385223388672, -2.7137370109558105, -1.0130387544631958, 2.1588258743286133, -0.6965282559394836, -0.5863328576087952, 5.682476043701172, -5.056402683258057, -0.9783533811569214, 1.5473753213882446, -2.2001280784606934, 3.601500988006592, 3.0746383666992188, 0.9094663858413696, -5.027466773986816, 0.1996650993824005, -0.22020965814590454, 0.8927829265594482, 2.7676286697387695, 3.913095235824585, -3.37308669090271, 0.7311697006225586, -1.8838980197906494, -2.642326831817627, -3.1619277000427246, -0.9289538860321045, 2.1357550621032715, -0.8898556232452393, -1.195042610168457, 1.1554468870162964, 1.2748795747756958, -4.026621341705322, 5.5519914627075195, -4.585369110107422, 4.026605129241943, 1.2044389247894287, -0.06486829370260239, 6.765420913696289, -2.342231512069702, 0.4368906617164612, -0.30990278720855713, 1.8998193740844727, 1.1213041543960571, 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and practitioners to learn key aspects of the young and rapidly growing body of research related to XAI, and review the existing approaches regarding the topic, discuss trends surrounding its sphere, and present major research trajectories.", "link": "dblp.org/rec/journals/access/AdadiB18", "authors": "Amina Adadi and M. 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recommendations, and decisions of opaque and complex machine learning systems. Increasingly academic libraries are providing library users with systems, services, and collections created and delivered by machine learning. Academic libraries should adopt XAI as a tool set to verify and validate these resources, and advocate for public policy regarding XAI that serves libraries, the academy, and the public interest.", "link": "", "authors": "M. 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comprehensive, state of the art introduction to the theory and practice of artificial intelligence for modern applications.", "link": "", "authors": "Stuart J. 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"Initially applying his concepts to simply defined artificial systems with limited numbers of parameters, Holland goes on to explore their use in the study of a wide range of complex, naturally occuring processes, concentrating on systems having multiple factors that interact in nonlinear ways.", "link": "dblp.org/rec/books/mit/H1992", "authors": "J. Holland", "year": "1992", "journal": "arXiv preprint", "embeddings": [-0.9352635741233826, -2.4602818489074707, 0.5212754011154175, 4.294469356536865, 0.12597200274467468, 0.7352782487869263, 0.4290064573287964, -1.4407618045806885, -1.0575225353240967, -1.7544668912887573, 1.3524727821350098, -0.7233592867851257, -0.5175272226333618, -4.0425238609313965, -1.9412025213241577, -0.24931807816028595, 2.3020825386047363, 1.4955601692199707, 2.3121185302734375, 2.591989278793335, -2.8232085704803467, 4.155322074890137, -6.927776336669922, -5.5541791915893555, 0.3930839002132416, 2.0166122913360596, 1.4028046131134033, -2.9723691940307617, -0.42331576347351074, 0.4283013939857483, -0.6433934569358826, -1.1268961429595947, 3.934133529663086, -7.914772033691406, 7.727320671081543, -4.454605579376221, -6.005181312561035, 4.643743515014648, 1.7195613384246826, -2.5821902751922607, 1.4183993339538574, 0.8748576641082764, 2.724611282348633, 1.6767522096633911, -1.1331021785736084, 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"link": "", "authors": "Daniel L. King and P. Delfabbro and J. Billieux and M. Potenza", "year": "2020", "journal": "Journal of Behavioral Addictions", "embeddings": [-2.0158724784851074, -2.1916117668151855, -1.5239089727401733, 3.3718018531799316, -0.1980663537979126, -4.969523906707764, 2.9580228328704834, -2.912370204925537, 0.16447384655475616, 1.9617480039596558, -0.824864387512207, -2.086271286010742, 2.8776750564575195, -0.7934310436248779, -4.498241901397705, -1.680261254310608, -3.6593902111053467, -1.9141075611114502, -4.1337666511535645, -2.3957154750823975, 0.20853939652442932, -3.6578879356384277, 0.36475250124931335, 0.399666965007782, -0.8955594897270203, -2.207740068435669, 1.4543367624282837, 0.22169245779514313, 2.089024543762207, -1.3691213130950928, -4.500672817230225, -3.6931090354919434, 1.9746686220169067, 0.9683632254600525, 3.6983227729797363, -3.9856576919555664, -4.035357475280762, 0.1876344531774521, -1.1469089984893799, 3.35810923576355, 0.5681931972503662, 2.724774122238159, -0.5377962589263916, -0.883069634437561, 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compulsive buying and higher than problem gambling.", "link": "", "authors": "Matthew W. R. Stevens and D. Dorstyn and P. Delfabbro and Daniel L. 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stigma to the millions of children who play video games as a part of a normal, healthy life and the healthy majority of gamers will be affected negatively.", "link": "", "authors": "Espen Aarseth and Anthony M. Bean and H. Boonen and Michelle Colder Carras and Mark C. Coulson and Dimitri Das and J. Deleuze and Elza Dunkels and J. Edman and C. Ferguson and M. Haagsma and Karin Helmersson Bergmark and Zaheer Hussain and J. Jansz and Daniel Kardefelt-Winther and L. Kutner and P. Markey and R. Nielsen and N. Prause and Andrew K. Przybylski and T. Quandt and A. Schimmenti and V. Starcevic and G. Stutman and Jan Van Looy and A. V. Van Rooij", "year": "2017", "journal": "Journal of Behavioral Addictions", "embeddings": [-1.0043680667877197, -0.45857638120651245, -3.2579333782196045, 3.963198184967041, -2.277491331100464, -0.32870978116989136, 0.6591950058937073, -2.077761173248291, 0.9301816821098328, 2.571948528289795, -4.384413719177246, -1.9644968509674072, 3.604799747467041, -0.8732833862304688, -4.195331573486328, 0.5307797193527222, 0.9195219874382019, -1.119083285331726, 0.5354745388031006, 0.5151053667068481, -0.05164128541946411, -0.45567789673805237, 1.539778709411621, -0.37112173438072205, -1.5034458637237549, 1.0308475494384766, 0.40727853775024414, 0.45361408591270447, 0.34336912631988525, 4.362488746643066, -5.359333515167236, -2.3167614936828613, 0.2867201268672943, 2.4331624507904053, 0.5763383507728577, -1.3690299987792969, 0.8284529447555542, 2.8682522773742676, -2.3773410320281982, 1.5536096096038818, 2.9871649742126465, 3.971527338027954, 2.1263413429260254, 2.511840581893921, 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gaming behavior was associated with examination-related stress and the belief that gaming helps combat stress, which highlights the need to focus on the coping style of the students to ascertain the likelihood of them engaging inGaming behavior as a coping mechanism against stress.", "link": "", "authors": "Y. Balhara and D. Kattula and Swarndeep Singh and Surekha Chukkali and R. Bhargava", "year": "2020", "journal": "Indian Journal of Public Health", "embeddings": [-1.2199867963790894, 0.6409810781478882, -4.102017879486084, 4.35006856918335, -2.2555365562438965, -2.417285680770874, 1.1481084823608398, -1.535430669784546, -1.7675598859786987, 0.07130473107099533, 1.5373342037200928, -2.7420220375061035, 5.780767917633057, -3.9906537532806396, -5.315666198730469, 3.2017276287078857, 0.615647554397583, -4.7427568435668945, 0.816792368888855, 0.823097825050354, 0.6117663383483887, -0.4836789667606354, 0.020778238773345947, -2.1625797748565674, -2.8581247329711914, -1.284501075744629, 3.3517565727233887, -2.2424871921539307, -1.3696913719177246, 2.5290427207946777, -5.507752895355225, -5.3302836418151855, 2.3808114528656006, 2.172969341278076, 2.108203887939453, -7.1873555183410645, -0.014131616801023483, 5.780705451965332, -3.739212989807129, 0.34182193875312805, -1.9105437994003296, 2.1271190643310547, 2.9693524837493896, -3.243802309036255, 0.37897545099258423, 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behaviour is significantly associated with a wide range of detrimental health-related outcomes.", "link": "", "authors": "Niko M\u00e4nnikk\u00f6 and Heidi Ruotsalainen and J. Miettunen and H. Pontes and M. 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studies, more effective for improving knowledge, skills, and satisfaction, however, the available evidence is mostly of low quality and calls for further rigorous, theory-driven research.", "link": "", "authors": "S. Gentry and Andrea Gauthier and Beatrice L'Estrade Ehrstrom and David Wortley and Anneliese Lilienthal and L. Tudor Car and Shoko Dauwels-Okutsu and C. K. Nikolaou and N. Zary and James Campbell and J. 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and be aware of how increased gaming during the pandemic may contribute to risk of gaming disorder.", "link": "", "authors": "C. Ko and J. Yen", "year": "2020", "journal": "Journal of Behavioral Addictions", "embeddings": [-2.2212138175964355, -2.1961169242858887, -2.1929128170013428, 5.661308288574219, 0.9278992414474487, -3.5348727703094482, 1.961771845817566, 0.9543482661247253, 1.5261512994766235, 1.9790832996368408, 0.8394849300384521, -0.1819061040878296, 2.048717498779297, -1.616469144821167, -2.3036320209503174, -1.747544527053833, -2.74088716506958, -0.8173270225524902, -2.301809310913086, -1.2044134140014648, 1.1587245464324951, -2.5421128273010254, 2.7856011390686035, -1.5039944648742676, -0.1859566569328308, -1.1920515298843384, 2.2509613037109375, 1.12479567527771, 4.520430564880371, -0.9341553449630737, -6.909679412841797, -2.733668327331543, 0.5865402221679688, 0.923551082611084, 2.9288787841796875, -5.1918230056762695, -2.655519485473633, 0.8510383367538452, -2.1651158332824707, 4.328912258148193, 1.8426077365875244, -0.1956852674484253, 2.7251198291778564, -0.04604634642601013, 1.2913738489151, 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and aetiology.", "link": "", "authors": "F. Paulus and S. Ohmann and A. von Gontard and C. Popow", "year": "2018", "journal": "Developmental Medicine \\& Child Neurology", "embeddings": [0.9634143710136414, -3.6837282180786133, -2.4200706481933594, 0.09410323202610016, -0.03378605842590332, -3.248307943344116, 1.631061315536499, -4.207371234893799, 3.7130348682403564, 1.9574671983718872, -5.746700763702393, -1.2385749816894531, 2.3499233722686768, 3.3485260009765625, -3.066070795059204, -1.5146255493164062, -4.868983745574951, -3.8145506381988525, -1.297310471534729, -0.2789832651615143, 2.18232798576355, 0.31656160950660706, 1.95560622215271, 2.386672019958496, 0.8629260063171387, -2.170069694519043, -3.0677778720855713, 2.719691753387451, 1.529456615447998, -0.7821691036224365, -6.69865608215332, -2.119255542755127, -0.45807361602783203, 5.228667259216309, 1.089316725730896, -3.4762935638427734, -3.1429576873779297, 2.085437536239624, -0.07053136825561523, 3.294266939163208, 4.302947521209717, -0.04439973831176758, 1.667048454284668, 4.435546875, 0.054012805223464966, 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approaches and findings around the gamification of information systems, and identify key synergies, opportunities, and questions for future research.", "link": "dblp.org/rec/conf/chi/DeterdingSNOD11", "authors": "Sebastian Deterding and M. Sicart and L. Nacke and K. O'hara and Dan Dixon", "year": "2011", "journal": "CHI Extended Abstracts", "embeddings": [-1.0388727188110352, -0.6106993556022644, -1.2227766513824463, 2.296140670776367, -0.99767005443573, 2.997537136077881, 2.1287245750427246, -2.8499505519866943, -1.2548699378967285, 0.13370415568351746, -3.460444211959839, -1.8922853469848633, 4.100735187530518, 0.24942775070667267, -1.9999799728393555, -2.181656837463379, 0.9381515383720398, -5.112270355224609, 0.5654864311218262, -1.118766188621521, -1.1211259365081787, -2.096602439880371, -1.2053768634796143, -0.421428918838501, -2.1931450366973877, -2.007370948791504, 1.898400902748108, 3.9730286598205566, 1.4225964546203613, 1.858546495437622, -0.7083282470703125, -2.0302329063415527, 4.486159324645996, -1.0971187353134155, 2.1304104328155518, -3.4159204959869385, -3.797330141067505, -0.3822965919971466, 1.6479634046554565, 1.4606881141662598, -1.3534330129623413, 2.2532715797424316, 0.40265345573425293, 0.57110995054245, -2.526088237762451, 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gaming disorder, and describes the intended meaning behind each of the nine DSM-5 criteria for internetGaming disorder.", "link": "", "authors": "N. Petry and F. Rehbein and D. Gentile and Jeroen S. Lemmens and H. Rumpf and T. M\u00f6\u00dfle and G. Bischof and R. Tao and D. Fung and Guilherme Borges and M. Auriacombe and Angels Gonz\u00e1lez Ib\u00e1\u00f1ez and Philip G. E. Tam and C. O'brien", "year": "2014", "journal": "Addiction", "embeddings": [-4.183728218078613, -2.155231475830078, -4.28864049911499, 2.8297529220581055, -3.3670921325683594, -0.6388591527938843, 0.14545461535453796, -2.6707522869110107, 1.6556035280227661, 0.6254622936248779, -4.292041301727295, -2.948695182800293, 4.399257659912109, 0.10395527631044388, -2.642869710922241, -4.024656295776367, -0.9713562726974487, -2.3167340755462646, -1.3733341693878174, -2.5071871280670166, 0.015479058027267456, 4.236396312713623, 0.12838691473007202, 0.48248207569122314, 0.2474622130393982, -0.8615916967391968, -1.487825632095337, 0.4183175563812256, 0.5343875288963318, 1.0506209135055542, -6.906103610992432, -2.4487149715423584, 0.30126333236694336, 0.4520350694656372, 4.461106300354004, -0.58547443151474, -4.49914026260376, 3.0695176124572754, -1.8726494312286377, 2.046454429626465, 3.4231619834899902, 1.8245309591293335, 1.7806158065795898, 5.337551593780518, 3.3194003105163574, 2.4920859336853027, 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maximum entropy reinforcement learning framework, and achieves state-of-the-art performance on a range of continuous control benchmark tasks, outperforming prior on-policy and off- policy methods.", "link": "dblp.org/rec/conf/icml/HaarnojaZAL18", "authors": "Tuomas Haarnoja and Aurick Zhou and P. Abbeel and S. Levine", "year": "2018", "journal": "International Conference on Machine Learning", "embeddings": [-2.1846365928649902, 1.059760570526123, 0.01126493513584137, 6.183737277984619, -3.7734975814819336, -1.047387719154358, 4.370643615722656, -5.408339023590088, -1.0588111877441406, -1.6673710346221924, -0.8031885623931885, 4.980506896972656, -0.2937842607498169, -2.689724922180176, -3.0733096599578857, 2.273068428039551, -1.4127277135849, 4.936955451965332, 2.6617960929870605, 2.0642285346984863, -3.5723876953125, 2.6822469234466553, -3.2748031616210938, -2.5915424823760986, -5.466987609863281, -0.4626120626926422, 3.5878219604492188, -0.7489619255065918, -2.8297948837280273, 3.9854795932769775, 0.7897613644599915, -3.0049352645874023, 5.362858772277832, -3.1675305366516113, 6.543251991271973, -1.6163475513458252, -3.340299367904663, 9.452805519104004, -0.015887558460235596, 3.3982906341552734, -0.8036012649536133, 2.2717339992523193, 1.3019726276397705, -0.2592700719833374, 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descent for optimization of deep neural network controllers and shows that asynchronous actor-critic succeeds on a wide variety of continuous motor control problems as well as on a new task of navigating random 3D mazes using a visual input.", "link": "dblp.org/rec/journals/corr/MnihBMGLHSK16", "authors": "Volodymyr Mnih and Adri\u00e0 Puigdom\u00e8nech Badia and Mehdi Mirza and A. Graves and T. Lillicrap and Tim Harley and David Silver and K. Kavukcuoglu", "year": "2016", "journal": "International Conference on Machine Learning", "embeddings": [-2.1374166011810303, -0.8020451664924622, 2.183562994003296, 4.623558044433594, -1.8454220294952393, -0.7713978886604309, 6.23721981048584, -3.8498423099517822, 0.18768885731697083, -0.7846459746360779, -1.7353676557540894, 6.035284042358398, 1.467812418937683, 0.0001822635531425476, -4.807483196258545, 0.6990434527397156, -1.7144088745117188, -2.5168867111206055, 2.6776912212371826, 1.9020373821258545, -1.7782646417617798, 1.48164701461792, -3.0962276458740234, -0.3992578983306885, -2.9897239208221436, -2.285416841506958, 3.25508189201355, 0.03879927843809128, -3.1113719940185547, 0.1277267336845398, 0.6391276121139526, -1.3613027334213257, 5.687127113342285, -4.730113983154297, 4.301339626312256, -1.3932969570159912, -4.702457904815674, 6.664841651916504, -4.4369683265686035, -1.12136971950531, -0.6729426383972168, 3.6262073516845703, 0.11384286731481552, 2.383350133895874, 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reinforcement learning, which outperforms all previous approaches on six of the games and surpasses a human expert on three of them.", "link": "dblp.org/rec/journals/corr/MnihKSGAWR13", "authors": "Volodymyr Mnih and K. Kavukcuoglu and David Silver and A. Graves and Ioannis Antonoglou and Daan Wierstra and Martin A. Riedmiller", "year": "2013", "journal": "arXiv.org", "embeddings": [-2.7389395236968994, -0.4655327796936035, 0.04073627293109894, 3.650351047515869, -3.828378915786743, 0.03870328888297081, 4.246326923370361, -7.769816875457764, -0.5740576982498169, 0.9278852343559265, -0.22913384437561035, 5.375112056732178, 2.420632839202881, 3.434521436691284, -3.548299551010132, 1.7003787755966187, -1.646679401397705, -0.2876848578453064, 1.7609561681747437, 1.7973989248275757, -3.0115835666656494, 1.1647371053695679, -2.221237897872925, 0.944710373878479, -5.495311737060547, -0.36396539211273193, 4.918084144592285, 1.6983070373535156, -1.3233990669250488, 0.04136054590344429, 2.9560036659240723, -2.8691108226776123, 5.826386451721191, -2.2700910568237305, 3.2568604946136475, 0.40666139125823975, -1.0045219659805298, 4.2822585105896, -3.505882978439331, -0.2550642788410187, -2.196725368499756, 1.417229175567627, -0.11554387956857681, 1.0403826236724854, 2.638680934906006, -2.870246410369873, 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machine learning algorithms in various fields, such as agricultural technology, personal authentication, wireless network, game, biometric recognition, and image recognition, are being improved and expanded in this paper.", "link": "dblp.org/rec/journals/jips/ParkP20d", "authors": "Ji Su Park and J. 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learning and deep learning, reinforcement methods on mitigating the selfish mining attacks in the blockchain, and the aspects of selection or exploration of the shortest branch of the blockchain when a fork occurs.", "link": "", "authors": "M. J. Jeyasheela Rakkini and K. Geetha", "year": "2022", "journal": "2022 IEEE 2nd Mysore Sub Section International Conference (MysuruCon)", "embeddings": [-4.470673561096191, 0.33175477385520935, -4.519050121307373, 7.808889389038086, 1.0430655479431152, -2.059809923171997, -2.180046319961548, -6.409491539001465, -1.2754340171813965, 0.25106602907180786, -2.780460834503174, -0.7087151408195496, 4.747013092041016, -3.8028340339660645, -3.6802260875701904, -3.479715585708618, -0.9412790536880493, -2.2840771675109863, 0.9181562066078186, 2.3814728260040283, -1.8783169984817505, 2.7956395149230957, 0.17616307735443115, -0.9155788421630859, -3.4390828609466553, -1.4879426956176758, 5.391064167022705, -1.717716932296753, -0.8079948425292969, -0.45075857639312744, 0.4794960916042328, -5.156922817230225, 1.8957191705703735, 1.9423105716705322, 3.3408122062683105, -4.725381374359131, -4.003656387329102, 7.470368385314941, -5.319914817810059, 3.6271932125091553, 2.8849377632141113, -1.416674017906189, 3.5410380363464355, 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over continuous action spaces, and demonstrates that for many of the tasks the algorithm can learn policies end-to-end: directly from raw pixel inputs.", "link": "dblp.org/rec/journals/corr/LillicrapHPHETS15", "authors": "T. Lillicrap and Jonathan J. Hunt and A. Pritzel and N. Heess and T. 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and shows that the resulting algorithm not only reduces the observed overestimations, as hypothesized, but that this also leads to much better performance on several games.", "link": "dblp.org/rec/journals/corr/HasseltGS15", "authors": "H. V. Hasselt and A. Guez and David Silver", "year": "2015", "journal": "AAAI Conference on Artificial Intelligence", "embeddings": [-4.061568260192871, 0.20475241541862488, -2.8180582523345947, 5.097324848175049, -3.466184377670288, -0.4413079023361206, 4.413756370544434, -7.330348014831543, -0.5759423971176147, 0.21532240509986877, -1.5086584091186523, 6.281774520874023, 2.0965652465820312, 1.7163556814193726, -3.4699811935424805, 1.29477858543396, -0.574381947517395, 0.9020941853523254, 3.9304726123809814, 2.086517810821533, -1.9703774452209473, 1.072445034980774, -4.363710403442383, -1.007921814918518, -4.014606475830078, -0.9168382287025452, 3.6711788177490234, 1.8481929302215576, -3.530515670776367, 1.0124249458312988, 3.3840625286102295, -2.737367630004883, 5.289729595184326, -4.531688213348389, 2.643031120300293, -1.7049753665924072, 0.19689230620861053, 7.800128936767578, -2.250610828399658, -0.8139504790306091, -1.9250695705413818, 2.5901758670806885, 1.4037264585494995, -0.33166563510894775, 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DQN) framework for the hybrid action space without approximation or relaxation, and combines the spirits of both D QN and DDPG by seamlessly integrating them.", "link": "dblp.org/rec/journals/corr/abs-1810-06394", "authors": "Jiechao Xiong and Qing Wang and Zhuoran Yang and Peng Sun and Lei Han and Yang Zheng and Haobo Fu and T. Zhang and Ji Liu and Han Liu", "year": "2018", "journal": "arXiv.org", "embeddings": [-2.404930830001831, 2.780529737472534, -3.476386547088623, 6.248407363891602, -1.9290434122085571, -0.9940251708030701, 5.054844379425049, -5.495333194732666, 0.18155035376548767, 0.7628745436668396, 1.9460748434066772, 1.4651962518692017, -2.1803362369537354, -1.6985589265823364, -6.170866966247559, 1.9948252439498901, 0.002340134233236313, 0.8409059047698975, 2.5934927463531494, -0.013787738978862762, -1.7127676010131836, 2.0414533615112305, -1.7425932884216309, -2.705146074295044, -2.721212387084961, -1.9245268106460571, 4.491169452667236, 3.2323648929595947, -2.3027164936065674, 1.2389661073684692, 3.5897905826568604, -0.1159806177020073, 6.590968132019043, -4.644930839538574, 2.9803712368011475, -2.0645155906677246, -3.9673335552215576, 5.468986988067627, -3.723846197128296, 1.096347689628601, -2.0231053829193115, 4.7104034423828125, -0.4647236168384552, 0.6541821956634521, 0.9131941795349121, 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x-ray of COVID-19 lung infection and may prove useful to stage lung disease severity, prognosticate, and predict treatment response and survival, thereby informing risk management and resource allocation.", "link": "", "authors": "Jocelyn Zhu and B. Shen and A. Abbasi and M. Hoshmand-Kochi and Haifang Li and T. 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or extra root in the distal roots of mandibular first molars.", "link": "", "authors": "T. Hiraiwa and Y. Ariji and M. Fukuda and Yoshitaka Kise and K. Nakata and A. Katsumata and H. Fujita and E. Ariji", "year": "2019", "journal": "Dento maxillo facial radiology", "embeddings": [3.715080976486206, -0.9701426029205322, -0.4579112231731415, 2.0414369106292725, -2.253495454788208, 4.709292411804199, 0.5273071527481079, 2.419583320617676, -0.6357923746109009, -1.940621256828308, -5.123598098754883, -0.8236778974533081, 2.1111655235290527, 1.832698106765747, -0.01216667890548706, -1.944261074066162, 1.5746772289276123, 1.1285479068756104, 0.9701478481292725, -1.0462723970413208, 1.9461262226104736, 4.172544479370117, -1.9539265632629395, -1.6379660367965698, -0.8310083150863647, 1.5974972248077393, 0.30344158411026, 1.2484618425369263, -1.6555659770965576, 5.116985321044922, -2.2829341888427734, -7.737582206726074, 5.386018753051758, -2.2938661575317383, -0.6267580986022949, 1.750577688217163, 1.9210870265960693, 8.99575424194336, -6.851428985595703, -4.731429576873779, 1.7431936264038086, 1.7558231353759766, 0.19001096487045288, 6.139934062957764, -1.7006926536560059, 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neural networks is explained, and how to get started with adopting deep learning into your own research activities to solve both new and old problems and build better, smarter consumer devices and services.", "link": "dblp.org/rec/journals/cem/LemleyBC17", "authors": "Joseph Lemley and S. Bazrafkan and P. Corcoran", "year": "2017", "journal": "IEEE Consumer Electronics Magazine", "embeddings": [-2.2308621406555176, -3.035897731781006, -1.1835885047912598, 6.988295555114746, -1.131081223487854, 2.171180248260498, 3.803689479827881, 1.095771074295044, -0.3682671785354614, -0.6045505404472351, -2.580979347229004, 1.9567594528198242, 3.096526622772217, 0.009142652153968811, -5.719169616699219, -0.8574284911155701, -2.2351338863372803, 1.609406590461731, 7.350208282470703, 2.6145989894866943, -1.8684698343276978, -1.4806339740753174, -2.2195842266082764, 1.1910886764526367, -4.5943803787231445, 1.244933843612671, -2.1563029289245605, 1.0251224040985107, -1.9373010396957397, -1.1957757472991943, 2.963399887084961, -3.626598834991455, 4.715202331542969, -6.00152587890625, 6.247568607330322, 2.1467862129211426, -2.804398775100708, 10.044960021972656, -3.9993581771850586, -1.2886017560958862, 5.350168704986572, 0.1267545521259308, 1.1842951774597168, 0.4023032486438751, 1.5438202619552612, 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autonomous things, especially autonomous driving vehicles, because they present a wide range of problems involving perception, decision, and actions that are very common in other autonomous things.", "link": "", "authors": "Cho Joonmyun", "year": "2020", "journal": "arXiv preprint", "embeddings": [-0.9594192504882812, -2.9439802169799805, 1.7118641138076782, 6.726092338562012, 1.3508409261703491, 0.26552146673202515, 5.64943790435791, -4.016297340393066, 0.6179718375205994, -4.102466106414795, -0.5212647318840027, 3.1041243076324463, 2.736083745956421, 0.7522634863853455, -3.99934720993042, -0.09466244280338287, 0.2092054784297943, 0.20248764753341675, 2.224792957305908, 0.816705584526062, -1.9147334098815918, -1.4992520809173584, -1.0957074165344238, -0.9730507135391235, -3.7463536262512207, -0.8479290008544922, 1.8027933835983276, 2.272730588912964, -1.545633316040039, -0.6427397727966309, 4.6626176834106445, -1.591017246246338, 2.6713123321533203, -5.754036903381348, 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{"paper_id": "sung2018facilitating", "title": "Facilitating deep-strategy behaviors and positive learning performances in science inquiry activities with a 3D experiential gaming approach", "abstract": "The experimental results showed that the students learning with the 3D experiential gaming system showed better learning achievements, problem-solving tendency, deep learning strategies, and deep learning motive than those who learned with the conventional technology-enhanced learning approach.", "link": "dblp.org/rec/journals/ile/SungHWL18", "authors": "Han-Yu Sung and Gwo-jen Hwang and Po-Han Wu and Dai-Chi Lin", "year": "2018", "journal": "Interactive Learning Environments", "embeddings": [-1.6397911310195923, -4.083800792694092, -2.270110607147217, 4.158763885498047, -1.884361982345581, 2.5272114276885986, 3.8728291988372803, -1.3945610523223877, -4.068872451782227, 0.7141156196594238, -2.953923225402832, 0.7320574522018433, 2.4807379245758057, 0.9795329570770264, 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Sridhar and V. 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deviation from the materials used in memory applications.", "link": "dblp.org/rec/journals/pieee/HaenschGP19", "authors": "W. Haensch and T. Gokmen and R. 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adopted in economic policy design, mechanism design, or economics at large. The AI Economist is a two-level, deep RL framework for policy design in which agents and a social planner coadapt. In particular, the AI Economist uses structured curriculum learning to stabilize the challenging two-level, coadaptive learning problem. We validate this framework in the domain of taxation. In one-step economies, the AI Economist recovers the optimal tax policy of economic theory. In spatiotemporal economies, the AI Economist substantially improves both utilitarian social welfare and the trade-off between equality and productivity over baselines. It does so despite emergent tax-gaming strategies while accounting for emergent labor specialization, agent interactions, and behavioral change. These results demonstrate that two-level, deep RL complements economic theory and unlocks an AI-based approach to designing and understanding economic policy.", "link": "", "authors": "Stephan Zheng and Alexander R. Trott and Sunil Srinivasa and David C. Parkes and R. Socher", "year": "2022", "journal": "Science Advances", "embeddings": [-3.011976957321167, 3.4472219944000244, -1.8129472732543945, 5.671018600463867, -2.988480567932129, -0.5341402292251587, 2.1658148765563965, -3.5072391033172607, 0.021604955196380615, -2.5010290145874023, 1.3625394105911255, -0.4665631055831909, 1.6099604368209839, -5.072071075439453, -4.881280422210693, 2.7131409645080566, 3.2629573345184326, 0.6759558320045471, 0.2695024013519287, 3.206839084625244, -4.486545562744141, 7.020160675048828, -3.1043310165405273, -3.981889247894287, -2.4638047218322754, -0.6833981275558472, 5.223614692687988, 0.48172879219055176, -0.7525392770767212, 2.1668405532836914, 0.7013121247291565, 0.4221677780151367, 4.344668388366699, -1.770456314086914, 5.9834747314453125, -4.749383926391602, -2.808462142944336, 3.6078577041625977, -0.30549800395965576, 0.11803198605775833, -0.3646138906478882, 1.4743304252624512, -2.0474934577941895, -1.7527947425842285, 2.263566493988037, 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Even leaders in the tech industry are beginning to decry the time young people spend on smartphones and social networks. Recently, the World Health Organization proposed adding \u201cgaming disorder\u201d to its official list of diseases, defining it as a pattern of gaming behavior so severe that it takes \u201cprecedence over other life interests\u201d. At the same time, many others have celebrated the positive properties of video games, social media, and social networks. This paper argues that a deeper understanding of human beings is needed to design for deep learning. For the purposes of this study \u201cdesign for deep learning\u201d means helping people matter and find meaning in ways that make them and others healthy in mind and body, while improving the state of the world for all living things, with due respect for truth, sensation, happiness, imagination, individuality, diversity, and the future. In particular, fifteen features related to human nature are suggested based on recent scientific developments to answer the question: What is a human being? Consequently, proposals that are linked to learning and transformation, as well as social improvement, should fit with the ways in which humans, as specific sorts of biological and social creatures, learn best (or can learn at all) and can change for the better. En la actualidad existe una nutrida controversia en relaci\u00f3n a los medios de comunicaci\u00f3n sociales y digitales que ha llevado, incluso, a censurar la utilizaci\u00f3n de las redes sociales y los m\u00f3viles por parte de l\u00edderes en la industria tecnol\u00f3gica. En este sentido, la Organizaci\u00f3n Mundial para la Salud ha propuesto a\u00f1adir el \u00abdesorden del juego\u00bb a su listado de enfermedades, defini\u00e9ndolo como un modelo de comportamiento de juego tan severo que se impone como \u00abpreferencia sobre otros intereses\u00bb. Al mismo tiempo, distintos acad\u00e9micos han enfatizado los aspectos positivos derivados de las redes sociales y los videojuegos. En este art\u00edculo se argumenta que es necesaria una mejor comprensi\u00f3n del ser humano para poder implementar lo que aqu\u00ed se define como dise\u00f1o para el aprendizaje profundo. El \u00abdise\u00f1o para el aprendizaje profundo\u00bb est\u00e1 encaminado al reconocimiento de las personas y el desarrollo de sentidos saludables, individual y colectivamente, as\u00ed como la mejora, en general, del estado del mundo para todos los seres vivos, seg\u00fan principios de verdad, felicidad, imaginaci\u00f3n, individualidad, diversidad y futuro. En particular, se sugieren quince caracter\u00edsticas basadas en desarrollos cient\u00edficos que responden a la pregunta: \u00bfQu\u00e9 es un ser humano? Consecuentemente, propuestas vinculadas al aprendizaje y la transformaci\u00f3n y mejora social deben ser coherentes con dichas caracter\u00edsticas que permiten definir c\u00f3mo las personas, en tanto que organismos biol\u00f3gicos y sociales, aprenden o pueden aprender \u00f3ptimamente, as\u00ed como cambiar para mejorar.", "link": "", "authors": "J. Gee and M. 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individual base stations and accordingly make intelligent cache decisions is developed, and a cooperation strategy for nearby base stations to collectively serve user requests is developed.", "link": "dblp.org/rec/conf/iwqos/PangLFS18", "authors": "Haitian Pang and Jiangchuan Liu and Xiaoyi Fan and Lifeng Sun", "year": "2018", "journal": "International Workshop on Quality of Service", "embeddings": [-6.585822105407715, -0.030280113220214844, -3.0293333530426025, 7.497102737426758, -0.5573853254318237, 0.5416561365127563, 3.4647793769836426, -1.874206304550171, 0.7704412937164307, -2.8344309329986572, -0.8010851740837097, 0.4534591734409332, 1.2516186237335205, -3.4909820556640625, -6.527171611785889, -3.235677719116211, -4.552760601043701, -1.5565279722213745, 0.9746913313865662, 2.3531627655029297, -3.5399060249328613, -0.2837090492248535, -0.8997272253036499, 2.7491443157196045, -2.4170591831207275, -1.7968688011169434, -0.8313014507293701, 0.8575950264930725, -1.223469614982605, 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-2.7148239612579346]}, "teo2018eeg": {"paper_id": "teo2018eeg", "title": "EEG-based excitement detection in immersive environments: An improved deep learning approach", "abstract": "A deep learning approach is used to improve the excitement detection rate to well above the 90% accuracy level, demonstrating the superiority of adopting a deepLearning approach over other machine learning approaches for detecting human excitement when immersed in an immersive virtual reality environment.", "link": "", "authors": "J. Teo and J. Chia", "year": "2018", "journal": "arXiv preprint", "embeddings": [-3.8234009742736816, -3.1352739334106445, 0.259141743183136, 4.245376110076904, -0.4517709016799927, 0.501214325428009, 5.0383172035217285, -5.953214645385742, 0.2540004551410675, -2.1031594276428223, -4.304662704467773, 2.845043182373047, 2.0420641899108887, 1.579838514328003, -2.3455963134765625, 0.6255365610122681, -1.7075424194335938, 1.426713228225708, -1.784283995628357, 1.0000660419464111, 1.294382095336914, -2.150644063949585, -1.4732309579849243, -0.5279548168182373, -2.0652005672454834, 0.9070104360580444, 1.9650394916534424, 1.4898765087127686, -1.8737845420837402, 0.6802130937576294, 0.239317387342453, -5.45419454574585, 2.7819275856018066, -2.5950303077697754, 2.590179443359375, 1.6936675310134888, -4.178639888763428, 8.597829818725586, -2.9125216007232666, -0.6519613265991211, 5.565265655517578, 3.1359293460845947, 3.5370771884918213, 0.4338066875934601, 3.4271960258483887, -3.5095584392547607, 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simple long-short-term-memory (LSTM) recurrent neural network (RNN).", "link": "dblp.org/rec/journals/corr/BreuerK17", "authors": "R. Breuer and R. Kimmel", "year": "2017", "journal": "arXiv.org", "embeddings": [-5.21569299697876, -2.909426689147949, -4.5238142013549805, 1.5099799633026123, 1.8810818195343018, 0.9621201157569885, 6.276888847351074, -1.4476755857467651, 0.8453189134597778, 0.3515222668647766, -2.890148401260376, 2.4965646266937256, 1.0663113594055176, 3.861574411392212, -4.651247024536133, -2.188060998916626, -0.6923270225524902, 2.5968844890594482, -0.49670353531837463, -1.6879005432128906, 2.234607696533203, 3.0266594886779785, -3.097363233566284, -1.313214898109436, -5.495388984680176, 0.750297486782074, -1.8717502355575562, 0.09797050803899765, 1.0062344074249268, 1.882819414138794, -0.45575278997421265, -6.582406997680664, 4.598669052124023, -1.3814581632614136, 2.576676607131958, 2.4743735790252686, -2.799342155456543, 7.259279727935791, -1.7249281406402588, -1.0361418724060059, 2.8575849533081055, 4.281418800354004, 2.7333030700683594, 1.5855228900909424, 3.1670491695404053, -0.35234951972961426, 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lightweight HUNL AI obtained with an end-to-end self-play reinforcement learning framework that adopts a pseudo-siamese architecture to directly learn from the input state information to the output actions by competing the learned model with its different historical versions.", "link": "dblp.org/rec/conf/aaai/ZhaoYLLX22", "authors": "Enmin Zhao and Renye Yan and Jinqiu Li and Kai Li and Junliang Xing", "year": "2022", "journal": "AAAI Conference on Artificial Intelligence", "embeddings": [-3.7807817459106445, 0.6095526218414307, 0.1962590366601944, 5.119630336761475, -2.9693098068237305, 0.3786500096321106, 2.591308116912842, -5.22594690322876, -1.5440438985824585, 1.804178237915039, 0.39686837792396545, 3.429173469543457, 1.2014977931976318, -2.161987543106079, -3.553072214126587, 0.7977229356765747, 0.9062284827232361, 1.7049208879470825, 1.5982978343963623, 2.8111214637756348, -2.758697509765625, 1.8569345474243164, -3.1233413219451904, -0.9237279891967773, -2.594434976577759, 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"dblp.org/rec/journals/tits/YangXKWGW22", "authors": "Xiaoxian Yang and Yueshen Xu and Li Kuang and Zhiying Wang and Honghao Gao and Xuejie Wang", "year": "2021", "journal": "IEEE transactions on intelligent transportation systems (Print)", "embeddings": [0.3247242569923401, -2.475078821182251, 1.6877070665359497, 6.142636299133301, -2.527568817138672, -1.849975824356079, 3.028081178665161, -3.5202102661132812, -0.7491348385810852, 0.1884167492389679, -1.7000765800476074, 1.3405861854553223, -1.0003635883331299, -6.9003071784973145, -1.5838799476623535, -0.05743785202503204, 0.26581498980522156, 0.3781544268131256, -0.9574320316314697, -1.7409265041351318, -3.8423550128936768, 5.832340240478516, -2.9341132640838623, -4.476290225982666, -2.8785808086395264, -1.4748151302337646, 6.434012413024902, 0.142990380525589, -2.2610952854156494, -3.4647834300994873, -0.8636211156845093, -0.1432587057352066, 4.449733257293701, 2.2990660667419434, 2.64943265914917, -2.497495651245117, 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Intelligence: Reinforcement Learning for Precision Dosing", "abstract": "A minireview of methodologies for achieving precision dosing with a focus on an artificial intelligence technique called reinforcement learning, which is currently used for individualizing dosing regimen in patients with life\u2010threatening diseases is proposed.", "link": "", "authors": "B. Ribba and S. Dudal and T. Lave\u0301 and R. Peck", "year": "2020", "journal": "Clinical pharmacology and therapy", "embeddings": [-3.8000144958496094, -5.528584957122803, 1.6346116065979004, 5.233468055725098, -1.3785029649734497, 0.21017077565193176, 0.7230963706970215, -0.4026640057563782, 0.962821364402771, -3.036799907684326, -0.7272945642471313, 2.1983931064605713, -0.5904591083526611, -1.3137484788894653, -6.114325523376465, -1.1075884103775024, -0.40693944692611694, 2.274240255355835, 0.6139504909515381, 2.995229721069336, -3.1441073417663574, 0.684975266456604, -2.7738659381866455, -2.667965888977051, 1.8078031539916992, -0.455173522233963, 0.623682975769043, -1.937477707862854, 2.4308247566223145, 2.2865488529205322, 0.3399994671344757, 2.517885446548462, 3.2237372398376465, -1.8657770156860352, 7.776942253112793, -3.675175905227661, -1.8604239225387573, 6.538679122924805, -3.3981308937072754, -1.3250161409378052, -0.2680743932723999, -1.7200061082839966, 1.761387825012207, 1.4312220811843872, 0.8535641431808472, 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three-dimensional (3D) beam model could enable rapid artificial intelligence-based optimization of deliverable treatment plans, reducing the time required for radiotherapy planning without requiring previous plans for training.", "link": "", "authors": "W. Hrinivich and Junghoon Lee", "year": "2020", "journal": "Medical Physics (Lancaster)", "embeddings": [-0.11445248126983643, -0.3194824457168579, -1.2767596244812012, 5.022140979766846, -0.1355189085006714, 1.9860601425170898, 0.021514471620321274, -0.5405572056770325, -3.6548404693603516, -2.211179256439209, 0.8787330389022827, 4.712231636047363, -0.4382648766040802, 1.0491173267364502, -5.058326721191406, 1.7882949113845825, 0.7245362997055054, 6.704866409301758, 0.6482033729553223, -0.40645119547843933, 0.2866404056549072, 4.1922287940979, 0.6704890727996826, -3.465226173400879, -2.8210501670837402, -3.9881327152252197, 1.0571882724761963, -1.220031499862671, -3.4171786308288574, 2.4946699142456055, 2.7742440700531006, -5.023104667663574, 4.642583847045898, -2.25386118888855, 6.757195472717285, -0.09619122743606567, -0.5537567138671875, 5.97275447845459, -5.140384197235107, -2.7636735439300537, 1.6203663349151611, 0.5711345672607422, 3.0095481872558594, 1.5578532218933105, 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maximize the expected accuracy of the generated architectures on a validation set.", "link": "dblp.org/rec/conf/iclr/ZophL17", "authors": "Barret Zoph and Quoc V. 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reinforcement learning models, forms the basis for the development of \"object saliency maps\", to provide visualization of internal states of DRLNs, thus enabling the formation of explanations and can be incorporated in any existing deep reinforcementlearning framework is proposed.", "link": "dblp.org/rec/journals/corr/abs-1809-06061", "authors": "R. Iyer and Yuezhang Li and Huao Li and M. Lewis and R. Sundar and K. Sycara", "year": "2018", "journal": "AAAI/ACM Conference on AI, Ethics, and Society", "embeddings": [-1.1176486015319824, 0.0066140517592430115, 1.0520004034042358, 4.826307773590088, 0.6523844003677368, -1.1504839658737183, 3.735119581222534, -2.4283177852630615, 1.5576772689819336, 1.5642906427383423, -3.5049190521240234, 3.840120792388916, 0.487742155790329, -0.4811840057373047, -2.7625460624694824, 2.767733097076416, 2.0562007427215576, 0.45621439814567566, 4.617573261260986, 2.1750400066375732, -0.215484157204628, 1.2117066383361816, -2.567902088165283, -2.1458232402801514, -1.3582650423049927, -2.050525188446045, 1.1038260459899902, 0.758863627910614, -0.30636999011039734, 2.227851152420044, -0.19927063584327698, -2.0280981063842773, 6.262097358703613, -2.6453475952148438, 5.033679962158203, -1.7244170904159546, -2.379485607147217, 3.6674232482910156, -5.331235408782959, 0.7281650304794312, 1.0429205894470215, 0.8227073550224304, -1.952024221420288, -2.131911277770996, 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a much better generalization ability in different network topologies.", "link": "dblp.org/rec/journals/icl/SunLLGH21", "authors": "Penghao Sun and Julong Lan and Junfei Li and Zehua Guo and Yuxiang Hu", "year": "2021", "journal": "IEEE Communications Letters", "embeddings": [-4.869658946990967, 0.9385348558425903, -2.9076485633850098, 6.846868515014648, 1.959558129310608, -0.25666967034339905, 2.4152069091796875, -6.241180419921875, 1.3185997009277344, -0.11068576574325562, 2.026139497756958, 1.2617852687835693, 1.0482138395309448, -4.035684108734131, -3.864044189453125, 1.0277870893478394, -2.581312894821167, 4.5240278244018555, -0.9788246154785156, 4.238579273223877, -3.133774757385254, 4.214409828186035, -2.8408117294311523, -2.8086233139038086, -2.1741673946380615, -4.605752468109131, 1.886388897895813, -0.7389065027236938, -2.3989996910095215, -2.608814239501953, 3.3104119300842285, -1.7379127740859985, 6.57390832901001, -1.1808496713638306, 7.064345836639404, -2.700986385345459, 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Reinforcement Learning", "abstract": "This work builds systems that feed each sensory input from the environment into distinct, but identical neural networks, each with no fixed relationship with one another, and shows that they can be trained to integrate information received locally, and through communication via an attention mechanism, can collectively produce a globally coherent policy.", "link": "dblp.org/rec/journals/corr/abs-2109-02869", "authors": "Yujin Tang and David R Ha", "year": "2021", "journal": "Neural Information Processing Systems", "embeddings": [-1.5520825386047363, -0.21147659420967102, 1.945500373840332, 4.61193323135376, -0.22538301348686218, -2.5401785373687744, 5.332982540130615, -2.0671980381011963, 2.520346164703369, -1.624894380569458, -0.9220805764198303, 2.616473436355591, 0.39706936478614807, -2.1076407432556152, -4.495115756988525, 1.301696538925171, 1.8772897720336914, 2.524848461151123, 2.4262635707855225, 2.1940369606018066, -0.25022706389427185, 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Arshad and Swetha Muniraju and E. Torkildson and Enrico Rantala and K. Doppler and Gang Zhou", "year": "2021", "journal": "ACM Trans. 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outperforms state-of-the-art GNN explainers and can be applied in the inductive setting, demonstrating its better generalization ability.", "link": "dblp.org/rec/conf/nips/ShanSZLL21", "authors": "Caihua Shan and Yifei Shen and Yao Zhang and Xiang Li and Dongsheng Li", "year": "2021", "journal": "Neural Information Processing Systems", "embeddings": [-3.3642539978027344, 3.64692759513855, 1.9734729528427124, 2.588502883911133, -0.06341509521007538, 1.4348080158233643, 2.2864084243774414, -3.6184678077697754, -0.04831309616565704, 3.2246432304382324, -2.1287002563476562, 3.360598564147949, -1.7468024492263794, -1.161569595336914, -4.293099880218506, 3.809886932373047, -1.4005708694458008, -0.1567639708518982, 0.040627218782901764, 1.8633644580841064, 1.4102494716644287, 1.6292412281036377, -1.137810230255127, -5.736350059509277, -1.8088953495025635, -5.360191345214844, 0.9965437650680542, -0.747299313545227, -4.23363733291626, -1.9040801525115967, 1.5361734628677368, -2.786478042602539, 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Circuit Designer: Transferable Transistor Sizing with Graph Neural Networks and Reinforcement Learning", "abstract": "This paper presents GCN-RL Circuit Designer, leveraging reinforcement learning (RL) to transfer the knowledge between different technology nodes and topologies, and demonstrates that RL with transfer learning can achieve much higher FoMs than methods without knowledge transfer.", "link": "dblp.org/rec/journals/corr/abs-2005-00406", "authors": "Hanrui Wang and Kuan Wang and Jiacheng Yang and Linxiao Shen and Nan Sun and Hae-Seung Lee and Song Han", "year": "2020", "journal": "Design Automation Conference", "embeddings": [-1.3568803071975708, 4.653128623962402, -3.8104870319366455, 4.119231224060059, 1.436911940574646, 0.3560887575149536, 2.603093147277832, -2.995043992996216, 3.907792568206787, 0.03564903140068054, -0.5547338724136353, 2.0060982704162598, 0.7171413898468018, -3.0532143115997314, -5.346816062927246, 0.5437121987342834, 1.4819124937057495, 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Kirkpatrick and Razvan Pascanu and Neil C. Rabinowitz and J. Veness and Guillaume Desjardins and Andrei A. Rusu and Kieran Milan and John Quan and Tiago Ramalho and A. Grabska-Barwinska and D. Hassabis and C. Clopath and D. Kumaran and R. Hadsell", "year": "2016", "journal": "Proceedings of the National Academy of Sciences of the United States of America", "embeddings": [-1.9311339855194092, -3.216376781463623, 2.036388397216797, 4.145429611206055, 0.22579830884933472, 1.274891972541809, 2.059175491333008, -2.922738552093506, -2.0962512493133545, 0.446290522813797, -0.4110870361328125, 6.718414306640625, 1.9226845502853394, 2.2345383167266846, -4.747903347015381, 0.2954249680042267, -0.7607731223106384, 0.13610908389091492, 4.1352949142456055, -0.7571770548820496, -0.22203654050827026, 1.1338715553283691, -1.070525884628296, -0.8627690672874451, -3.2449584007263184, 0.21545150876045227, 1.6959419250488281, -0.8127392530441284, -5.280799865722656, 1.9582499265670776, -0.03225626051425934, -4.646201133728027, 3.7369463443756104, -4.005359649658203, 4.741666793823242, -2.4246368408203125, -2.4562931060791016, 6.943797588348389, -3.5580062866210938, -1.7598812580108643, -0.45654237270355225, 2.1148293018341064, 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reinforcement learning method for Node Injection Poisoning Attacks (NIPA), to sequentially modify the labels and links of the injected nodes, without changing the connectivity between existing nodes, is proposed.", "link": "dblp.org/rec/conf/www/SunWTHH20", "authors": "Yiwei Sun and Suhang Wang and Xianfeng Tang and Tsung-Yu Hsieh and Vasant G Honavar", "year": "2020", "journal": "The Web Conference", "embeddings": [-4.012135982513428, -0.8431494235992432, -3.5825772285461426, 5.710937976837158, -2.5942885875701904, -3.8354499340057373, 3.5584843158721924, -1.426619291305542, -1.9117846488952637, 0.4588161110877991, -6.072989463806152, 3.3515050411224365, 0.6602378487586975, -2.842733144760132, -5.412811279296875, 0.6597950458526611, -3.318634510040283, 1.5440353155136108, 1.8570713996887207, 2.6764891147613525, 0.008106380701065063, 1.5566208362579346, -1.3413646221160889, -5.035281181335449, -5.728743076324463, -4.932411193847656, 0.0032858550548553467, -0.6175190210342407, 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-1.4217199087142944, -1.958526849746704, -4.581465721130371]}, "yakan2022analysis": {"paper_id": "yakan2022analysis", "title": "Analysis of Development of Artificial Intelligence in the Game Industry", "abstract": "The goal of this research was to figure out how artificial intelligence was progressing in the gaming business.", "link": "", "authors": "Sayid Adli Yakan", "year": "2022", "journal": "International Journal of Cyber and IT Service Management", "embeddings": [-0.031294163316488266, -1.31574285030365, -0.3436734676361084, 2.6134848594665527, 0.3588621914386749, 2.8693339824676514, 0.6098235845565796, -1.8995922803878784, 0.7617852091789246, -1.1455326080322266, -3.372138500213623, -0.5124702453613281, 5.536169528961182, -5.018396377563477, -1.470543622970581, 0.8752520084381104, 1.3746838569641113, -2.6181015968322754, 3.904656171798706, 1.2148191928863525, -0.6063251495361328, 0.39740389585494995, -4.091867923736572, -0.3447083830833435, 0.30927905440330505, 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Pereira and R. Prada and Ana Paiva and S. Louchart and N. Suttie and T. Lim and Ricardo Lopes and Rafael Bidarra and F. Bellotti and M. Kravc\u00edk and Maria Cristina Ferreira de Oliveira", "year": "2021", "journal": "Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment", "embeddings": [0.08463907241821289, -1.8361501693725586, 1.0392720699310303, 3.2169411182403564, -0.30733081698417664, 1.5868151187896729, 2.799145460128784, -2.0877504348754883, -1.9396332502365112, -0.7164432406425476, -2.200092315673828, -0.22842726111412048, -1.0430017709732056, -0.44873160123825073, -2.6924092769622803, 2.155712604522705, -0.432465136051178, -3.2218985557556152, 2.950587272644043, -1.3242135047912598, 0.28757360577583313, -0.2432677149772644, -2.864330530166626, 0.3004544973373413, 0.8302299976348877, -2.8556151390075684, 0.9980997443199158, 5.7987165451049805, 1.600658655166626, 0.4362281560897827, -0.5220495462417603, -1.7155003547668457, 3.661898136138916, -2.9376823902130127, 2.1504311561584473, 0.28765326738357544, -5.520986557006836, 2.254112482070923, 1.6512064933776855, 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applications of the AI-XR combination are identified, including autonomous cars, robotics, military, medical training, cancer diagnosis, entertainment, and gaming applications, advanced visualization methods, smart homes, affective computing, and driver education and training.", "link": "dblp.org/rec/journals/frvir/ReinersDKC21", "authors": "D. Reiners and Mohammad Reza Davahli and W. Karwowski and C. Cruz-Neira", "year": "2021", "journal": "Frontiers in Virtual Reality", "embeddings": [-0.39603573083877563, -4.301392078399658, 0.4060657024383545, 5.496870040893555, -1.0791003704071045, 0.5287944674491882, 4.5147247314453125, -5.004574298858643, -0.7019086480140686, -3.1189537048339844, -1.860844373703003, 3.661410331726074, -2.3144500255584717, 1.7195146083831787, -5.043763160705566, -1.3213956356048584, -1.5315773487091064, 0.44839563965797424, 1.3931866884231567, -3.4497809410095215, -0.8665827512741089, 1.6123273372650146, -4.714659690856934, -0.6428954005241394, 1.199975848197937, 2.2355995178222656, 2.855799436569214, 1.5535523891448975, 8.14398193359375, 0.616179347038269, 1.9052531719207764, -2.13238263130188, 3.7887089252471924, -5.091536521911621, 1.7527284622192383, 1.0016831159591675, -4.716109275817871, 1.606093406677246, 0.6576598882675171, -1.832415223121643, 4.078629970550537, 3.407440185546875, -2.989337682723999, -0.20487958192825317, 2.074275016784668, 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suspect, and how to evolve the interaction between human and artificial intelligence.", "link": "", "authors": "J. Hanley", "year": "2021", "journal": "arXiv preprint", "embeddings": [0.6823248267173767, -1.2637308835983276, 0.08675752580165863, 1.0128521919250488, 0.5137075781822205, 2.7225308418273926, -0.6740744113922119, -3.1072468757629395, -2.09747314453125, 1.3614115715026855, -5.204672336578369, -0.23136214911937714, -1.708367109298706, -3.5332159996032715, -2.7597477436065674, 6.59502649307251, -1.9438380002975464, -4.610437393188477, 1.0273253917694092, 2.772233247756958, -1.7995675802230835, 4.511386394500732, -6.631457805633545, -2.935025453567505, 2.7792348861694336, -0.638782262802124, 0.9564023613929749, 1.3846484422683716, 0.19524142146110535, 1.5187455415725708, 1.1040358543395996, -2.2324163913726807, 4.824666500091553, -2.917001724243164, 5.214646816253662, -2.981123208999634, -2.23797345161438, 8.436229705810547, 1.9986683130264282, -0.23829956352710724, 0.8163347244262695, 2.9940524101257324, 0.6464263796806335, -0.5944698452949524, 1.4117928743362427, -0.052459750324487686, 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physicians\u2019 capabilities.", "link": "", "authors": "Y. Mintz and R. Brodie", "year": "2019", "journal": "MITAT. 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presented.", "link": "", "authors": "A. Zakaryan", "year": "2021", "journal": "arXiv preprint", "embeddings": [2.176973819732666, -2.4601104259490967, 3.157531261444092, 2.864516019821167, 1.7917317152023315, 5.553699493408203, 1.6857941150665283, -4.155726909637451, -2.2121284008026123, -2.1968142986297607, -2.62162446975708, -0.6739275455474854, 2.3803000450134277, -1.8758994340896606, -1.3480643033981323, 2.238330841064453, 0.2683868706226349, 0.5306039452552795, 0.5639875531196594, -0.3775442838668823, -0.6206501722335815, 3.803541421890259, -1.3481669425964355, -2.2076873779296875, 4.799308776855469, -2.2985687255859375, 3.554058074951172, -2.316880702972412, 0.1815274953842163, 0.6984751224517822, -1.573569655418396, -2.0804848670959473, -0.3701023757457733, -5.228110313415527, 5.139701843261719, 2.8125617504119873, -4.408866882324219, 3.266444206237793, 0.5886505842208862, -1.1425381898880005, 1.1771857738494873, 2.584205150604248, 1.5114306211471558, 6.939377784729004, 5.873893737792969, -3.065751791000366, 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College in New Hampshire to thrash out a plan for emulating the thought processes of the human mind.", "link": "", "authors": "C. Edwards", "year": "2021", "journal": "Engineering \\& Technology", "embeddings": [1.4706923961639404, -0.10477831959724426, 4.321481704711914, 1.2623233795166016, 3.1368257999420166, 4.014975547790527, 3.2890825271606445, -5.629961967468262, 0.5307819247245789, -0.44315633177757263, -2.1062045097351074, 1.341850996017456, 2.0964300632476807, -3.039285182952881, -1.9660838842391968, 1.9254909753799438, -0.03840996325016022, 1.1720478534698486, 1.4823404550552368, 2.493267297744751, -0.4956207573413849, 1.8753077983856201, -1.5353878736495972, 0.11939549446105957, -0.43829017877578735, -1.6281527280807495, 2.5812785625457764, -3.429117202758789, -1.4226024150848389, 4.069969654083252, -1.164245367050171, -4.597405910491943, 2.0505285263061523, -5.241212844848633, 4.643004417419434, 0.684015691280365, -3.9705021381378174, 2.82558536529541, 1.9858226776123047, -2.8429644107818604, 1.2064920663833618, 4.049310684204102, 0.9585626125335693, 3.732667922973633, 4.49608039855957, 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mathematical model of human cognition, which store experimental knowledge from task examples through a process of learning.", "link": "", "authors": "M. Akash and Fiitjee", "year": "2015", "journal": "arXiv preprint", "embeddings": [0.6382445096969604, -1.3918662071228027, 3.349945068359375, 2.7723679542541504, 2.986672878265381, 1.7650692462921143, 3.706648826599121, -4.683613300323486, 0.2649749517440796, 0.6350023746490479, -2.774038553237915, 2.916804790496826, 2.6609044075012207, -4.108601093292236, -2.378263235092163, 2.1239092350006104, -0.8490360975265503, -1.0559985637664795, 3.376643657684326, 3.024902105331421, 3.029461145401001, -1.0603878498077393, -3.818236827850342, -2.8869216442108154, 0.19358688592910767, -0.5495703220367432, 0.5800276398658752, -5.410533428192139, -3.324807643890381, -0.10203370451927185, -2.996922731399536, -4.636884689331055, 4.176648139953613, -1.6149647235870361, 4.7097930908203125, -0.8134499788284302, -5.055102348327637, 3.211815118789673, 0.3214022219181061, -1.5593597888946533, 2.758286476135254, 0.8562902808189392, 0.7187132835388184, 4.797065734863281, 3.9721174240112305, 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datasets.", "link": "", "authors": "Hoida Ali Abdalgadir Ahmed and Mohammed Hassen Hamza", "year": "2011", "journal": "arXiv preprint", "embeddings": [-0.3567524552345276, -2.2683029174804688, 0.3962222635746002, 2.0266220569610596, 0.34277158975601196, -0.625262975692749, -0.718142032623291, -1.0341932773590088, -3.2866344451904297, 0.23918375372886658, -1.7941603660583496, 2.3282880783081055, 3.5759754180908203, -2.139819383621216, -2.477874279022217, 1.9276245832443237, -1.5523905754089355, 2.8538994789123535, 2.9147565364837646, -0.18066173791885376, -0.3462896943092346, 4.082645893096924, 0.21263957023620605, -3.623433828353882, 1.568121075630188, -2.093332052230835, 1.6873804330825806, -4.445868968963623, -0.6646429300308228, 1.117492914199829, -1.7457889318466187, -4.781529426574707, 2.9125375747680664, -2.226893663406372, 1.3692560195922852, 1.0878748893737793, 1.3838677406311035, 3.767835855484009, -3.916987895965576, -1.7847281694412231, -0.841137707233429, 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in Neural Networks, its strengths, weaknesses and applications are explained.", "link": "", "authors": "Indranarain Ramlall", "year": "2009", "journal": "arXiv preprint", "embeddings": [1.3487216234207153, -2.7849514484405518, 0.4687933921813965, 3.4720146656036377, 1.0505297183990479, 0.8382109999656677, 3.9836337566375732, -6.547352313995361, -0.18984165787696838, 0.4462268352508545, -1.6890878677368164, 2.962836742401123, 1.9720227718353271, -3.6398708820343018, -2.1885762214660645, 1.4334051609039307, -1.3968390226364136, 1.052119493484497, 2.0703678131103516, 0.8425674438476562, -1.4538977146148682, 0.8552258014678955, -2.6136980056762695, -1.9873313903808594, 1.2292863130569458, -2.0022106170654297, 0.06218987703323364, -3.2970170974731445, -0.01784953474998474, -0.0025654174387454987, -3.6112759113311768, -2.046914577484131, 4.903047561645508, -2.0809743404388428, 6.262293338775635, 0.9951944351196289, -2.8581643104553223, 5.9482221603393555, -4.283493995666504, 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0000000000000000000000000000000000000000..48bb380209723febf8100f28bc567f8cacab691c --- /dev/null +++ b/latex-flatten.py @@ -0,0 +1,50 @@ +#!/usr/bin/env python +# This script is taken from: https://github.com/rekka/latex-flatten + +# A simple script for flattening LaTeX files by inlining included files. +# +# - Supports `\include` and `\input` commands. +# - Automatically adds extension `.tex` if the file does not have an extension. +# - Handles multiple include commands per line, comments. +# - Does not flatten recursively. + +import re +import sys + +if len(sys.argv)==3: + main_name = sys.argv[1] + output_name = sys.argv[2] +else: + sys.exit('USAGE: %s main.tex output.tex' %sys.argv[0]) + +main = open(main_name,'r') +output = open(output_name,'w') + +for line in main.readlines(): + s = re.split('%', line, 2) + tex = s[0] + if len(s) > 1: + comment = '%' + s[1] + else: + comment = '' + + chunks = re.split(r'\\(?:input|include)\{[^}]+\}', tex) + + if len(chunks) > 1: + for (c, t) in zip(chunks, re.finditer(r'\\(input|include)\{([^}]+)\}', tex)): + cmd_name = t.group(1) + include_name = t.group(2) + if '.' not in include_name: include_name = include_name + '.tex' + if c.strip(): output.write(c + '\n') + output.write('% BEGIN \\' + cmd_name + '{' + include_name + '}\n') + include = open(include_name, 'r') + output.write(include.read()) + include.close() + output.write('% END \\' + cmd_name + '{' + include_name + '}\n') + tail = chunks[-1] + comment + if tail.strip(): output.write(tail) + else: + output.write(line) + +output.close() +main.close() \ No newline at end of file diff --git a/latex_templates/ICLR2022/abstract.tex b/latex_templates/ICLR2022/abstract.tex new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/latex_templates/ICLR2022/backgrounds.tex b/latex_templates/ICLR2022/backgrounds.tex new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/latex_templates/ICLR2022/conclusion.tex b/latex_templates/ICLR2022/conclusion.tex new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/latex_templates/ICLR2022/experiments.tex b/latex_templates/ICLR2022/experiments.tex new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/latex_templates/ICLR2022/fancyhdr.sty b/latex_templates/ICLR2022/fancyhdr.sty new file mode 100644 index 0000000000000000000000000000000000000000..77ed4e3012d822c7cca5c17efcae308b32b8cc2b --- /dev/null +++ b/latex_templates/ICLR2022/fancyhdr.sty @@ -0,0 +1,485 @@ +% fancyhdr.sty version 3.2 +% Fancy headers and footers for LaTeX. +% Piet van Oostrum, +% Dept of Computer and Information Sciences, University of Utrecht, +% Padualaan 14, P.O. Box 80.089, 3508 TB Utrecht, The Netherlands +% Telephone: +31 30 2532180. Email: piet@cs.uu.nl +% ======================================================================== +% LICENCE: +% This file may be distributed under the terms of the LaTeX Project Public +% License, as described in lppl.txt in the base LaTeX distribution. +% Either version 1 or, at your option, any later version. +% ======================================================================== +% MODIFICATION HISTORY: +% Sep 16, 1994 +% version 1.4: Correction for use with \reversemargin +% Sep 29, 1994: +% version 1.5: Added the \iftopfloat, \ifbotfloat and \iffloatpage commands +% Oct 4, 1994: +% version 1.6: Reset single spacing in headers/footers for use with +% setspace.sty or doublespace.sty +% Oct 4, 1994: +% version 1.7: changed \let\@mkboth\markboth to +% \def\@mkboth{\protect\markboth} to make it more robust +% Dec 5, 1994: +% version 1.8: corrections for amsbook/amsart: define \@chapapp and (more +% importantly) use the \chapter/sectionmark definitions from ps@headings if +% they exist (which should be true for all standard classes). +% May 31, 1995: +% version 1.9: The proposed \renewcommand{\headrulewidth}{\iffloatpage... +% construction in the doc did not work properly with the fancyplain style. +% June 1, 1995: +% version 1.91: The definition of \@mkboth wasn't restored on subsequent +% \pagestyle{fancy}'s. +% June 1, 1995: +% version 1.92: The sequence \pagestyle{fancyplain} \pagestyle{plain} +% \pagestyle{fancy} would erroneously select the plain version. +% June 1, 1995: +% version 1.93: \fancypagestyle command added. +% Dec 11, 1995: +% version 1.94: suggested by Conrad Hughes +% CJCH, Dec 11, 1995: added \footruleskip to allow control over footrule +% position (old hardcoded value of .3\normalbaselineskip is far too high +% when used with very small footer fonts). +% Jan 31, 1996: +% version 1.95: call \@normalsize in the reset code if that is defined, +% otherwise \normalsize. +% this is to solve a problem with ucthesis.cls, as this doesn't +% define \@currsize. Unfortunately for latex209 calling \normalsize doesn't +% work as this is optimized to do very little, so there \@normalsize should +% be called. Hopefully this code works for all versions of LaTeX known to +% mankind. +% April 25, 1996: +% version 1.96: initialize \headwidth to a magic (negative) value to catch +% most common cases that people change it before calling \pagestyle{fancy}. +% Note it can't be initialized when reading in this file, because +% \textwidth could be changed afterwards. This is quite probable. +% We also switch to \MakeUppercase rather than \uppercase and introduce a +% \nouppercase command for use in headers. and footers. +% May 3, 1996: +% version 1.97: Two changes: +% 1. Undo the change in version 1.8 (using the pagestyle{headings} defaults +% for the chapter and section marks. The current version of amsbook and +% amsart classes don't seem to need them anymore. Moreover the standard +% latex classes don't use \markboth if twoside isn't selected, and this is +% confusing as \leftmark doesn't work as expected. +% 2. include a call to \ps@empty in ps@@fancy. This is to solve a problem +% in the amsbook and amsart classes, that make global changes to \topskip, +% which are reset in \ps@empty. Hopefully this doesn't break other things. +% May 7, 1996: +% version 1.98: +% Added % after the line \def\nouppercase +% May 7, 1996: +% version 1.99: This is the alpha version of fancyhdr 2.0 +% Introduced the new commands \fancyhead, \fancyfoot, and \fancyhf. +% Changed \headrulewidth, \footrulewidth, \footruleskip to +% macros rather than length parameters, In this way they can be +% conditionalized and they don't consume length registers. There is no need +% to have them as length registers unless you want to do calculations with +% them, which is unlikely. Note that this may make some uses of them +% incompatible (i.e. if you have a file that uses \setlength or \xxxx=) +% May 10, 1996: +% version 1.99a: +% Added a few more % signs +% May 10, 1996: +% version 1.99b: +% Changed the syntax of \f@nfor to be resistent to catcode changes of := +% Removed the [1] from the defs of \lhead etc. because the parameter is +% consumed by the \@[xy]lhead etc. macros. +% June 24, 1997: +% version 1.99c: +% corrected \nouppercase to also include the protected form of \MakeUppercase +% \global added to manipulation of \headwidth. +% \iffootnote command added. +% Some comments added about \@fancyhead and \@fancyfoot. +% Aug 24, 1998 +% version 1.99d +% Changed the default \ps@empty to \ps@@empty in order to allow +% \fancypagestyle{empty} redefinition. +% Oct 11, 2000 +% version 2.0 +% Added LPPL license clause. +% +% A check for \headheight is added. An errormessage is given (once) if the +% header is too large. Empty headers don't generate the error even if +% \headheight is very small or even 0pt. +% Warning added for the use of 'E' option when twoside option is not used. +% In this case the 'E' fields will never be used. +% +% Mar 10, 2002 +% version 2.1beta +% New command: \fancyhfoffset[place]{length} +% defines offsets to be applied to the header/footer to let it stick into +% the margins (if length > 0). +% place is like in fancyhead, except that only E,O,L,R can be used. +% This replaces the old calculation based on \headwidth and the marginpar +% area. +% \headwidth will be dynamically calculated in the headers/footers when +% this is used. +% +% Mar 26, 2002 +% version 2.1beta2 +% \fancyhfoffset now also takes h,f as possible letters in the argument to +% allow the header and footer widths to be different. +% New commands \fancyheadoffset and \fancyfootoffset added comparable to +% \fancyhead and \fancyfoot. +% Errormessages and warnings have been made more informative. +% +% Dec 9, 2002 +% version 2.1 +% The defaults for \footrulewidth, \plainheadrulewidth and +% \plainfootrulewidth are changed from \z@skip to 0pt. In this way when +% someone inadvertantly uses \setlength to change any of these, the value +% of \z@skip will not be changed, rather an errormessage will be given. + +% March 3, 2004 +% Release of version 3.0 + +% Oct 7, 2004 +% version 3.1 +% Added '\endlinechar=13' to \fancy@reset to prevent problems with +% includegraphics in header when verbatiminput is active. + +% March 22, 2005 +% version 3.2 +% reset \everypar (the real one) in \fancy@reset because spanish.ldf does +% strange things with \everypar between << and >>. + +\def\ifancy@mpty#1{\def\temp@a{#1}\ifx\temp@a\@empty} + +\def\fancy@def#1#2{\ifancy@mpty{#2}\fancy@gbl\def#1{\leavevmode}\else + \fancy@gbl\def#1{#2\strut}\fi} + +\let\fancy@gbl\global + +\def\@fancyerrmsg#1{% + \ifx\PackageError\undefined + \errmessage{#1}\else + \PackageError{Fancyhdr}{#1}{}\fi} +\def\@fancywarning#1{% + \ifx\PackageWarning\undefined + \errmessage{#1}\else + \PackageWarning{Fancyhdr}{#1}{}\fi} + +% Usage: \@forc \var{charstring}{command to be executed for each char} +% This is similar to LaTeX's \@tfor, but expands the charstring. + +\def\@forc#1#2#3{\expandafter\f@rc\expandafter#1\expandafter{#2}{#3}} +\def\f@rc#1#2#3{\def\temp@ty{#2}\ifx\@empty\temp@ty\else + \f@@rc#1#2\f@@rc{#3}\fi} +\def\f@@rc#1#2#3\f@@rc#4{\def#1{#2}#4\f@rc#1{#3}{#4}} + +% Usage: \f@nfor\name:=list\do{body} +% Like LaTeX's \@for but an empty list is treated as a list with an empty +% element + +\newcommand{\f@nfor}[3]{\edef\@fortmp{#2}% + \expandafter\@forloop#2,\@nil,\@nil\@@#1{#3}} + +% Usage: \def@ult \cs{defaults}{argument} +% sets \cs to the characters from defaults appearing in argument +% or defaults if it would be empty. All characters are lowercased. + +\newcommand\def@ult[3]{% + \edef\temp@a{\lowercase{\edef\noexpand\temp@a{#3}}}\temp@a + \def#1{}% + \@forc\tmpf@ra{#2}% + {\expandafter\if@in\tmpf@ra\temp@a{\edef#1{#1\tmpf@ra}}{}}% + \ifx\@empty#1\def#1{#2}\fi} +% +% \if@in +% +\newcommand{\if@in}[4]{% + \edef\temp@a{#2}\def\temp@b##1#1##2\temp@b{\def\temp@b{##1}}% + \expandafter\temp@b#2#1\temp@b\ifx\temp@a\temp@b #4\else #3\fi} + +\newcommand{\fancyhead}{\@ifnextchar[{\f@ncyhf\fancyhead h}% + {\f@ncyhf\fancyhead h[]}} +\newcommand{\fancyfoot}{\@ifnextchar[{\f@ncyhf\fancyfoot f}% + {\f@ncyhf\fancyfoot f[]}} +\newcommand{\fancyhf}{\@ifnextchar[{\f@ncyhf\fancyhf{}}% + {\f@ncyhf\fancyhf{}[]}} + +% New commands for offsets added + +\newcommand{\fancyheadoffset}{\@ifnextchar[{\f@ncyhfoffs\fancyheadoffset h}% + {\f@ncyhfoffs\fancyheadoffset h[]}} +\newcommand{\fancyfootoffset}{\@ifnextchar[{\f@ncyhfoffs\fancyfootoffset f}% + {\f@ncyhfoffs\fancyfootoffset f[]}} +\newcommand{\fancyhfoffset}{\@ifnextchar[{\f@ncyhfoffs\fancyhfoffset{}}% + {\f@ncyhfoffs\fancyhfoffset{}[]}} + +% The header and footer fields are stored in command sequences with +% names of the form: \f@ncy with for [eo], from [lcr] +% and from [hf]. + +\def\f@ncyhf#1#2[#3]#4{% + \def\temp@c{}% + \@forc\tmpf@ra{#3}% + {\expandafter\if@in\tmpf@ra{eolcrhf,EOLCRHF}% + {}{\edef\temp@c{\temp@c\tmpf@ra}}}% + \ifx\@empty\temp@c\else + \@fancyerrmsg{Illegal char `\temp@c' in \string#1 argument: + [#3]}% + \fi + \f@nfor\temp@c{#3}% + {\def@ult\f@@@eo{eo}\temp@c + \if@twoside\else + \if\f@@@eo e\@fancywarning + {\string#1's `E' option without twoside option is useless}\fi\fi + \def@ult\f@@@lcr{lcr}\temp@c + \def@ult\f@@@hf{hf}{#2\temp@c}% + \@forc\f@@eo\f@@@eo + {\@forc\f@@lcr\f@@@lcr + {\@forc\f@@hf\f@@@hf + {\expandafter\fancy@def\csname + f@ncy\f@@eo\f@@lcr\f@@hf\endcsname + {#4}}}}}} + +\def\f@ncyhfoffs#1#2[#3]#4{% + \def\temp@c{}% + \@forc\tmpf@ra{#3}% + {\expandafter\if@in\tmpf@ra{eolrhf,EOLRHF}% + {}{\edef\temp@c{\temp@c\tmpf@ra}}}% + \ifx\@empty\temp@c\else + \@fancyerrmsg{Illegal char `\temp@c' in \string#1 argument: + [#3]}% + \fi + \f@nfor\temp@c{#3}% + {\def@ult\f@@@eo{eo}\temp@c + \if@twoside\else + \if\f@@@eo e\@fancywarning + {\string#1's `E' option without twoside option is useless}\fi\fi + \def@ult\f@@@lcr{lr}\temp@c + \def@ult\f@@@hf{hf}{#2\temp@c}% + \@forc\f@@eo\f@@@eo + {\@forc\f@@lcr\f@@@lcr + {\@forc\f@@hf\f@@@hf + {\expandafter\setlength\csname + f@ncyO@\f@@eo\f@@lcr\f@@hf\endcsname + {#4}}}}}% + \fancy@setoffs} + +% Fancyheadings version 1 commands. These are more or less deprecated, +% but they continue to work. + +\newcommand{\lhead}{\@ifnextchar[{\@xlhead}{\@ylhead}} +\def\@xlhead[#1]#2{\fancy@def\f@ncyelh{#1}\fancy@def\f@ncyolh{#2}} +\def\@ylhead#1{\fancy@def\f@ncyelh{#1}\fancy@def\f@ncyolh{#1}} + +\newcommand{\chead}{\@ifnextchar[{\@xchead}{\@ychead}} +\def\@xchead[#1]#2{\fancy@def\f@ncyech{#1}\fancy@def\f@ncyoch{#2}} +\def\@ychead#1{\fancy@def\f@ncyech{#1}\fancy@def\f@ncyoch{#1}} + +\newcommand{\rhead}{\@ifnextchar[{\@xrhead}{\@yrhead}} +\def\@xrhead[#1]#2{\fancy@def\f@ncyerh{#1}\fancy@def\f@ncyorh{#2}} +\def\@yrhead#1{\fancy@def\f@ncyerh{#1}\fancy@def\f@ncyorh{#1}} + +\newcommand{\lfoot}{\@ifnextchar[{\@xlfoot}{\@ylfoot}} +\def\@xlfoot[#1]#2{\fancy@def\f@ncyelf{#1}\fancy@def\f@ncyolf{#2}} +\def\@ylfoot#1{\fancy@def\f@ncyelf{#1}\fancy@def\f@ncyolf{#1}} + +\newcommand{\cfoot}{\@ifnextchar[{\@xcfoot}{\@ycfoot}} +\def\@xcfoot[#1]#2{\fancy@def\f@ncyecf{#1}\fancy@def\f@ncyocf{#2}} +\def\@ycfoot#1{\fancy@def\f@ncyecf{#1}\fancy@def\f@ncyocf{#1}} + +\newcommand{\rfoot}{\@ifnextchar[{\@xrfoot}{\@yrfoot}} +\def\@xrfoot[#1]#2{\fancy@def\f@ncyerf{#1}\fancy@def\f@ncyorf{#2}} +\def\@yrfoot#1{\fancy@def\f@ncyerf{#1}\fancy@def\f@ncyorf{#1}} + +\newlength{\fancy@headwidth} +\let\headwidth\fancy@headwidth +\newlength{\f@ncyO@elh} +\newlength{\f@ncyO@erh} +\newlength{\f@ncyO@olh} +\newlength{\f@ncyO@orh} +\newlength{\f@ncyO@elf} +\newlength{\f@ncyO@erf} +\newlength{\f@ncyO@olf} +\newlength{\f@ncyO@orf} +\newcommand{\headrulewidth}{0.4pt} +\newcommand{\footrulewidth}{0pt} +\newcommand{\footruleskip}{.3\normalbaselineskip} + +% Fancyplain stuff shouldn't be used anymore (rather +% \fancypagestyle{plain} should be used), but it must be present for +% compatibility reasons. + +\newcommand{\plainheadrulewidth}{0pt} +\newcommand{\plainfootrulewidth}{0pt} +\newif\if@fancyplain \@fancyplainfalse +\def\fancyplain#1#2{\if@fancyplain#1\else#2\fi} + +\headwidth=-123456789sp %magic constant + +% Command to reset various things in the headers: +% a.o. single spacing (taken from setspace.sty) +% and the catcode of ^^M (so that epsf files in the header work if a +% verbatim crosses a page boundary) +% It also defines a \nouppercase command that disables \uppercase and +% \Makeuppercase. It can only be used in the headers and footers. +\let\fnch@everypar\everypar% save real \everypar because of spanish.ldf +\def\fancy@reset{\fnch@everypar{}\restorecr\endlinechar=13 + \def\baselinestretch{1}% + \def\nouppercase##1{{\let\uppercase\relax\let\MakeUppercase\relax + \expandafter\let\csname MakeUppercase \endcsname\relax##1}}% + \ifx\undefined\@newbaseline% NFSS not present; 2.09 or 2e + \ifx\@normalsize\undefined \normalsize % for ucthesis.cls + \else \@normalsize \fi + \else% NFSS (2.09) present + \@newbaseline% + \fi} + +% Initialization of the head and foot text. + +% The default values still contain \fancyplain for compatibility. +\fancyhf{} % clear all +% lefthead empty on ``plain'' pages, \rightmark on even, \leftmark on odd pages +% evenhead empty on ``plain'' pages, \leftmark on even, \rightmark on odd pages +\if@twoside + \fancyhead[el,or]{\fancyplain{}{\sl\rightmark}} + \fancyhead[er,ol]{\fancyplain{}{\sl\leftmark}} +\else + \fancyhead[l]{\fancyplain{}{\sl\rightmark}} + \fancyhead[r]{\fancyplain{}{\sl\leftmark}} +\fi +\fancyfoot[c]{\rm\thepage} % page number + +% Use box 0 as a temp box and dimen 0 as temp dimen. +% This can be done, because this code will always +% be used inside another box, and therefore the changes are local. + +\def\@fancyvbox#1#2{\setbox0\vbox{#2}\ifdim\ht0>#1\@fancywarning + {\string#1 is too small (\the#1): ^^J Make it at least \the\ht0.^^J + We now make it that large for the rest of the document.^^J + This may cause the page layout to be inconsistent, however\@gobble}% + \dimen0=#1\global\setlength{#1}{\ht0}\ht0=\dimen0\fi + \box0} + +% Put together a header or footer given the left, center and +% right text, fillers at left and right and a rule. +% The \lap commands put the text into an hbox of zero size, +% so overlapping text does not generate an errormessage. +% These macros have 5 parameters: +% 1. LEFTSIDE BEARING % This determines at which side the header will stick +% out. When \fancyhfoffset is used this calculates \headwidth, otherwise +% it is \hss or \relax (after expansion). +% 2. \f@ncyolh, \f@ncyelh, \f@ncyolf or \f@ncyelf. This is the left component. +% 3. \f@ncyoch, \f@ncyech, \f@ncyocf or \f@ncyecf. This is the middle comp. +% 4. \f@ncyorh, \f@ncyerh, \f@ncyorf or \f@ncyerf. This is the right component. +% 5. RIGHTSIDE BEARING. This is always \relax or \hss (after expansion). + +\def\@fancyhead#1#2#3#4#5{#1\hbox to\headwidth{\fancy@reset + \@fancyvbox\headheight{\hbox + {\rlap{\parbox[b]{\headwidth}{\raggedright#2}}\hfill + \parbox[b]{\headwidth}{\centering#3}\hfill + \llap{\parbox[b]{\headwidth}{\raggedleft#4}}}\headrule}}#5} + +\def\@fancyfoot#1#2#3#4#5{#1\hbox to\headwidth{\fancy@reset + \@fancyvbox\footskip{\footrule + \hbox{\rlap{\parbox[t]{\headwidth}{\raggedright#2}}\hfill + \parbox[t]{\headwidth}{\centering#3}\hfill + \llap{\parbox[t]{\headwidth}{\raggedleft#4}}}}}#5} + +\def\headrule{{\if@fancyplain\let\headrulewidth\plainheadrulewidth\fi + \hrule\@height\headrulewidth\@width\headwidth \vskip-\headrulewidth}} + +\def\footrule{{\if@fancyplain\let\footrulewidth\plainfootrulewidth\fi + \vskip-\footruleskip\vskip-\footrulewidth + \hrule\@width\headwidth\@height\footrulewidth\vskip\footruleskip}} + +\def\ps@fancy{% +\@ifundefined{@chapapp}{\let\@chapapp\chaptername}{}%for amsbook +% +% Define \MakeUppercase for old LaTeXen. +% Note: we used \def rather than \let, so that \let\uppercase\relax (from +% the version 1 documentation) will still work. +% +\@ifundefined{MakeUppercase}{\def\MakeUppercase{\uppercase}}{}% +\@ifundefined{chapter}{\def\sectionmark##1{\markboth +{\MakeUppercase{\ifnum \c@secnumdepth>\z@ + \thesection\hskip 1em\relax \fi ##1}}{}}% +\def\subsectionmark##1{\markright {\ifnum \c@secnumdepth >\@ne + \thesubsection\hskip 1em\relax \fi ##1}}}% +{\def\chaptermark##1{\markboth {\MakeUppercase{\ifnum \c@secnumdepth>\m@ne + \@chapapp\ \thechapter. \ \fi ##1}}{}}% +\def\sectionmark##1{\markright{\MakeUppercase{\ifnum \c@secnumdepth >\z@ + \thesection. \ \fi ##1}}}}% +%\csname ps@headings\endcsname % use \ps@headings defaults if they exist +\ps@@fancy +\gdef\ps@fancy{\@fancyplainfalse\ps@@fancy}% +% Initialize \headwidth if the user didn't +% +\ifdim\headwidth<0sp +% +% This catches the case that \headwidth hasn't been initialized and the +% case that the user added something to \headwidth in the expectation that +% it was initialized to \textwidth. We compensate this now. This loses if +% the user intended to multiply it by a factor. But that case is more +% likely done by saying something like \headwidth=1.2\textwidth. +% The doc says you have to change \headwidth after the first call to +% \pagestyle{fancy}. This code is just to catch the most common cases were +% that requirement is violated. +% + \global\advance\headwidth123456789sp\global\advance\headwidth\textwidth +\fi} +\def\ps@fancyplain{\ps@fancy \let\ps@plain\ps@plain@fancy} +\def\ps@plain@fancy{\@fancyplaintrue\ps@@fancy} +\let\ps@@empty\ps@empty +\def\ps@@fancy{% +\ps@@empty % This is for amsbook/amsart, which do strange things with \topskip +\def\@mkboth{\protect\markboth}% +\def\@oddhead{\@fancyhead\fancy@Oolh\f@ncyolh\f@ncyoch\f@ncyorh\fancy@Oorh}% +\def\@oddfoot{\@fancyfoot\fancy@Oolf\f@ncyolf\f@ncyocf\f@ncyorf\fancy@Oorf}% +\def\@evenhead{\@fancyhead\fancy@Oelh\f@ncyelh\f@ncyech\f@ncyerh\fancy@Oerh}% +\def\@evenfoot{\@fancyfoot\fancy@Oelf\f@ncyelf\f@ncyecf\f@ncyerf\fancy@Oerf}% +} +% Default definitions for compatibility mode: +% These cause the header/footer to take the defined \headwidth as width +% And to shift in the direction of the marginpar area + +\def\fancy@Oolh{\if@reversemargin\hss\else\relax\fi} +\def\fancy@Oorh{\if@reversemargin\relax\else\hss\fi} +\let\fancy@Oelh\fancy@Oorh +\let\fancy@Oerh\fancy@Oolh + +\let\fancy@Oolf\fancy@Oolh +\let\fancy@Oorf\fancy@Oorh +\let\fancy@Oelf\fancy@Oelh +\let\fancy@Oerf\fancy@Oerh + +% New definitions for the use of \fancyhfoffset +% These calculate the \headwidth from \textwidth and the specified offsets. + +\def\fancy@offsolh{\headwidth=\textwidth\advance\headwidth\f@ncyO@olh + \advance\headwidth\f@ncyO@orh\hskip-\f@ncyO@olh} +\def\fancy@offselh{\headwidth=\textwidth\advance\headwidth\f@ncyO@elh + \advance\headwidth\f@ncyO@erh\hskip-\f@ncyO@elh} + +\def\fancy@offsolf{\headwidth=\textwidth\advance\headwidth\f@ncyO@olf + \advance\headwidth\f@ncyO@orf\hskip-\f@ncyO@olf} +\def\fancy@offself{\headwidth=\textwidth\advance\headwidth\f@ncyO@elf + \advance\headwidth\f@ncyO@erf\hskip-\f@ncyO@elf} + +\def\fancy@setoffs{% +% Just in case \let\headwidth\textwidth was used + \fancy@gbl\let\headwidth\fancy@headwidth + \fancy@gbl\let\fancy@Oolh\fancy@offsolh + \fancy@gbl\let\fancy@Oelh\fancy@offselh + \fancy@gbl\let\fancy@Oorh\hss + \fancy@gbl\let\fancy@Oerh\hss + \fancy@gbl\let\fancy@Oolf\fancy@offsolf + \fancy@gbl\let\fancy@Oelf\fancy@offself + \fancy@gbl\let\fancy@Oorf\hss + \fancy@gbl\let\fancy@Oerf\hss} + +\newif\iffootnote +\let\latex@makecol\@makecol +\def\@makecol{\ifvoid\footins\footnotetrue\else\footnotefalse\fi +\let\topfloat\@toplist\let\botfloat\@botlist\latex@makecol} +\def\iftopfloat#1#2{\ifx\topfloat\empty #2\else #1\fi} +\def\ifbotfloat#1#2{\ifx\botfloat\empty #2\else #1\fi} +\def\iffloatpage#1#2{\if@fcolmade #1\else #2\fi} + +\newcommand{\fancypagestyle}[2]{% + \@namedef{ps@#1}{\let\fancy@gbl\relax#2\relax\ps@fancy}} diff --git a/latex_templates/ICLR2022/fig.png b/latex_templates/ICLR2022/fig.png new file mode 100644 index 0000000000000000000000000000000000000000..61141907f9164cf762226c43c05a7d681212a767 Binary files /dev/null and b/latex_templates/ICLR2022/fig.png differ diff --git a/latex_templates/ICLR2022/iclr2022_conference.bst b/latex_templates/ICLR2022/iclr2022_conference.bst new file mode 100644 index 0000000000000000000000000000000000000000..149a48c5be151e84bc9f0f4ecb1381875e71573e --- /dev/null +++ b/latex_templates/ICLR2022/iclr2022_conference.bst @@ -0,0 +1,1440 @@ +%% File: `iclr2017.bst' +%% A copy of iclm2010.bst, which is a modification of `plainnl.bst' for use with natbib package +%% +%% Copyright 2010 Hal Daum\'e III +%% Modified by J. Fürnkranz +%% - Changed labels from (X and Y, 2000) to (X & Y, 2000) +%% +%% Copyright 1993-2007 Patrick W Daly +%% Max-Planck-Institut f\"ur Sonnensystemforschung +%% Max-Planck-Str. 2 +%% D-37191 Katlenburg-Lindau +%% Germany +%% E-mail: daly@mps.mpg.de +%% +%% This program can be redistributed and/or modified under the terms +%% of the LaTeX Project Public License Distributed from CTAN +%% archives in directory macros/latex/base/lppl.txt; either +%% version 1 of the License, or any later version. +%% + % Version and source file information: + % \ProvidesFile{icml2010.mbs}[2007/11/26 1.93 (PWD)] + % + % BibTeX `plainnat' family + % version 0.99b for BibTeX versions 0.99a or later, + % for LaTeX versions 2.09 and 2e. + % + % For use with the `natbib.sty' package; emulates the corresponding + % member of the `plain' family, but with author-year citations. + % + % With version 6.0 of `natbib.sty', it may also be used for numerical + % citations, while retaining the commands \citeauthor, \citefullauthor, + % and \citeyear to print the corresponding information. + % + % For version 7.0 of `natbib.sty', the KEY field replaces missing + % authors/editors, and the date is left blank in \bibitem. + % + % Includes field EID for the sequence/citation number of electronic journals + % which is used instead of page numbers. + % + % Includes fields ISBN and ISSN. + % + % Includes field URL for Internet addresses. + % + % Includes field DOI for Digital Object Idenfifiers. + % + % Works best with the url.sty package of Donald Arseneau. + % + % Works with identical authors and year are further sorted by + % citation key, to preserve any natural sequence. + % +ENTRY + { address + author + booktitle + chapter + doi + eid + edition + editor + howpublished + institution + isbn + issn + journal + key + month + note + number + organization + pages + publisher + school + series + title + type + url + volume + year + } + {} + { label extra.label sort.label short.list } + +INTEGERS { output.state before.all mid.sentence after.sentence after.block } + +FUNCTION {init.state.consts} +{ #0 'before.all := + #1 'mid.sentence := + #2 'after.sentence := + #3 'after.block := +} + +STRINGS { s t } + +FUNCTION {output.nonnull} +{ 's := + output.state mid.sentence = + { ", " * write$ } + { output.state after.block = + { add.period$ write$ + newline$ + "\newblock " write$ + } + { output.state before.all = + 'write$ + { add.period$ " " * write$ } + if$ + } + if$ + mid.sentence 'output.state := + } + if$ + s +} + +FUNCTION {output} +{ duplicate$ empty$ + 'pop$ + 'output.nonnull + if$ +} + +FUNCTION {output.check} +{ 't := + duplicate$ empty$ + { pop$ "empty " t * " in " * cite$ * warning$ } + 'output.nonnull + if$ +} + +FUNCTION {fin.entry} +{ add.period$ + write$ + newline$ +} + +FUNCTION {new.block} +{ output.state before.all = + 'skip$ + { after.block 'output.state := } + if$ +} + +FUNCTION {new.sentence} +{ output.state after.block = + 'skip$ + { output.state before.all = + 'skip$ + { after.sentence 'output.state := } + if$ + } + if$ +} + +FUNCTION {not} +{ { #0 } + { #1 } + if$ +} + +FUNCTION {and} +{ 'skip$ + { pop$ #0 } + if$ +} + +FUNCTION {or} +{ { pop$ #1 } + 'skip$ + if$ +} + +FUNCTION {new.block.checka} +{ empty$ + 'skip$ + 'new.block + if$ +} + +FUNCTION {new.block.checkb} +{ empty$ + swap$ empty$ + and + 'skip$ + 'new.block + if$ +} + +FUNCTION {new.sentence.checka} +{ empty$ + 'skip$ + 'new.sentence + if$ +} + +FUNCTION {new.sentence.checkb} +{ empty$ + swap$ empty$ + and + 'skip$ + 'new.sentence + if$ +} + +FUNCTION {field.or.null} +{ duplicate$ empty$ + { pop$ "" } + 'skip$ + if$ +} + +FUNCTION {emphasize} +{ duplicate$ empty$ + { pop$ "" } + { "\emph{" swap$ * "}" * } + if$ +} + +INTEGERS { nameptr namesleft numnames } + +FUNCTION {format.names} +{ 's := + #1 'nameptr := + s num.names$ 'numnames := + numnames 'namesleft := + { namesleft #0 > } + { s nameptr "{ff~}{vv~}{ll}{, jj}" format.name$ 't := + nameptr #1 > + { namesleft #1 > + { ", " * t * } + { numnames #2 > + { "," * } + 'skip$ + if$ + t "others" = + { " et~al." * } + { " and " * t * } + if$ + } + if$ + } + 't + if$ + nameptr #1 + 'nameptr := + namesleft #1 - 'namesleft := + } + while$ +} + +FUNCTION {format.key} +{ empty$ + { key field.or.null } + { "" } + if$ +} + +FUNCTION {format.authors} +{ author empty$ + { "" } + { author format.names } + if$ +} + +FUNCTION {format.editors} +{ editor empty$ + { "" } + { editor format.names + editor num.names$ #1 > + { " (eds.)" * } + { " (ed.)" * } + if$ + } + if$ +} + +FUNCTION {format.isbn} +{ isbn empty$ + { "" } + { new.block "ISBN " isbn * } + if$ +} + +FUNCTION {format.issn} +{ issn empty$ + { "" } + { new.block "ISSN " issn * } + if$ +} + +FUNCTION {format.url} +{ url empty$ + { "" } + { new.block "URL \url{" url * "}" * } + if$ +} + +FUNCTION {format.doi} +{ doi empty$ + { "" } + { new.block "\doi{" doi * "}" * } + if$ +} + +FUNCTION {format.title} +{ title empty$ + { "" } + { title "t" change.case$ } + if$ +} + +FUNCTION {format.full.names} +{'s := + #1 'nameptr := + s num.names$ 'numnames := + numnames 'namesleft := + { namesleft #0 > } + { s nameptr + "{vv~}{ll}" format.name$ 't := + nameptr #1 > + { + namesleft #1 > + { ", " * t * } + { + numnames #2 > + { "," * } + 'skip$ + if$ + t "others" = + { " et~al." * } + { " and " * t * } + if$ + } + if$ + } + 't + if$ + nameptr #1 + 'nameptr := + namesleft #1 - 'namesleft := + } + while$ +} + +FUNCTION {author.editor.full} +{ author empty$ + { editor empty$ + { "" } + { editor format.full.names } + if$ + } + { author format.full.names } + if$ +} + +FUNCTION {author.full} +{ author empty$ + { "" } + { author format.full.names } + if$ +} + +FUNCTION {editor.full} +{ editor empty$ + { "" } + { editor format.full.names } + if$ +} + +FUNCTION {make.full.names} +{ type$ "book" = + type$ "inbook" = + or + 'author.editor.full + { type$ "proceedings" = + 'editor.full + 'author.full + if$ + } + if$ +} + +FUNCTION {output.bibitem} +{ newline$ + "\bibitem[" write$ + label write$ + ")" make.full.names duplicate$ short.list = + { pop$ } + { * } + if$ + "]{" * write$ + cite$ write$ + "}" write$ + newline$ + "" + before.all 'output.state := +} + +FUNCTION {n.dashify} +{ 't := + "" + { t empty$ not } + { t #1 #1 substring$ "-" = + { t #1 #2 substring$ "--" = not + { "--" * + t #2 global.max$ substring$ 't := + } + { { t #1 #1 substring$ "-" = } + { "-" * + t #2 global.max$ substring$ 't := + } + while$ + } + if$ + } + { t #1 #1 substring$ * + t #2 global.max$ substring$ 't := + } + if$ + } + while$ +} + +FUNCTION {format.date} +{ year duplicate$ empty$ + { "empty year in " cite$ * warning$ + pop$ "" } + 'skip$ + if$ + month empty$ + 'skip$ + { month + " " * swap$ * + } + if$ + extra.label * +} + +FUNCTION {format.btitle} +{ title emphasize +} + +FUNCTION {tie.or.space.connect} +{ duplicate$ text.length$ #3 < + { "~" } + { " " } + if$ + swap$ * * +} + +FUNCTION {either.or.check} +{ empty$ + 'pop$ + { "can't use both " swap$ * " fields in " * cite$ * warning$ } + if$ +} + +FUNCTION {format.bvolume} +{ volume empty$ + { "" } + { "volume" volume tie.or.space.connect + series empty$ + 'skip$ + { " of " * series emphasize * } + if$ + "volume and number" number either.or.check + } + if$ +} + +FUNCTION {format.number.series} +{ volume empty$ + { number empty$ + { series field.or.null } + { output.state mid.sentence = + { "number" } + { "Number" } + if$ + number tie.or.space.connect + series empty$ + { "there's a number but no series in " cite$ * warning$ } + { " in " * series * } + if$ + } + if$ + } + { "" } + if$ +} + +FUNCTION {format.edition} +{ edition empty$ + { "" } + { output.state mid.sentence = + { edition "l" change.case$ " edition" * } + { edition "t" change.case$ " edition" * } + if$ + } + if$ +} + +INTEGERS { multiresult } + +FUNCTION {multi.page.check} +{ 't := + #0 'multiresult := + { multiresult not + t empty$ not + and + } + { t #1 #1 substring$ + duplicate$ "-" = + swap$ duplicate$ "," = + swap$ "+" = + or or + { #1 'multiresult := } + { t #2 global.max$ substring$ 't := } + if$ + } + while$ + multiresult +} + +FUNCTION {format.pages} +{ pages empty$ + { "" } + { pages multi.page.check + { "pp.\ " pages n.dashify tie.or.space.connect } + { "pp.\ " pages tie.or.space.connect } + if$ + } + if$ +} + +FUNCTION {format.eid} +{ eid empty$ + { "" } + { "art." eid tie.or.space.connect } + if$ +} + +FUNCTION {format.vol.num.pages} +{ volume field.or.null + number empty$ + 'skip$ + { "\penalty0 (" number * ")" * * + volume empty$ + { "there's a number but no volume in " cite$ * warning$ } + 'skip$ + if$ + } + if$ + pages empty$ + 'skip$ + { duplicate$ empty$ + { pop$ format.pages } + { ":\penalty0 " * pages n.dashify * } + if$ + } + if$ +} + +FUNCTION {format.vol.num.eid} +{ volume field.or.null + number empty$ + 'skip$ + { "\penalty0 (" number * ")" * * + volume empty$ + { "there's a number but no volume in " cite$ * warning$ } + 'skip$ + if$ + } + if$ + eid empty$ + 'skip$ + { duplicate$ empty$ + { pop$ format.eid } + { ":\penalty0 " * eid * } + if$ + } + if$ +} + +FUNCTION {format.chapter.pages} +{ chapter empty$ + 'format.pages + { type empty$ + { "chapter" } + { type "l" change.case$ } + if$ + chapter tie.or.space.connect + pages empty$ + 'skip$ + { ", " * format.pages * } + if$ + } + if$ +} + +FUNCTION {format.in.ed.booktitle} +{ booktitle empty$ + { "" } + { editor empty$ + { "In " booktitle emphasize * } + { "In " format.editors * ", " * booktitle emphasize * } + if$ + } + if$ +} + +FUNCTION {empty.misc.check} +{ author empty$ title empty$ howpublished empty$ + month empty$ year empty$ note empty$ + and and and and and + key empty$ not and + { "all relevant fields are empty in " cite$ * warning$ } + 'skip$ + if$ +} + +FUNCTION {format.thesis.type} +{ type empty$ + 'skip$ + { pop$ + type "t" change.case$ + } + if$ +} + +FUNCTION {format.tr.number} +{ type empty$ + { "Technical Report" } + 'type + if$ + number empty$ + { "t" change.case$ } + { number tie.or.space.connect } + if$ +} + +FUNCTION {format.article.crossref} +{ key empty$ + { journal empty$ + { "need key or journal for " cite$ * " to crossref " * crossref * + warning$ + "" + } + { "In \emph{" journal * "}" * } + if$ + } + { "In " } + if$ + " \citet{" * crossref * "}" * +} + +FUNCTION {format.book.crossref} +{ volume empty$ + { "empty volume in " cite$ * "'s crossref of " * crossref * warning$ + "In " + } + { "Volume" volume tie.or.space.connect + " of " * + } + if$ + editor empty$ + editor field.or.null author field.or.null = + or + { key empty$ + { series empty$ + { "need editor, key, or series for " cite$ * " to crossref " * + crossref * warning$ + "" * + } + { "\emph{" * series * "}" * } + if$ + } + 'skip$ + if$ + } + 'skip$ + if$ + " \citet{" * crossref * "}" * +} + +FUNCTION {format.incoll.inproc.crossref} +{ editor empty$ + editor field.or.null author field.or.null = + or + { key empty$ + { booktitle empty$ + { "need editor, key, or booktitle for " cite$ * " to crossref " * + crossref * warning$ + "" + } + { "In \emph{" booktitle * "}" * } + if$ + } + { "In " } + if$ + } + { "In " } + if$ + " \citet{" * crossref * "}" * +} + +FUNCTION {article} +{ output.bibitem + format.authors "author" output.check + author format.key output + new.block + format.title "title" output.check + new.block + crossref missing$ + { journal emphasize "journal" output.check + eid empty$ + { format.vol.num.pages output } + { format.vol.num.eid output } + if$ + format.date "year" output.check + } + { format.article.crossref output.nonnull + eid empty$ + { format.pages output } + { format.eid output } + if$ + } + if$ + format.issn output + format.doi output + format.url output + new.block + note output + fin.entry +} + +FUNCTION {book} +{ output.bibitem + author empty$ + { format.editors "author and editor" output.check + editor format.key output + } + { format.authors output.nonnull + crossref missing$ + { "author and editor" editor either.or.check } + 'skip$ + if$ + } + if$ + new.block + format.btitle "title" output.check + crossref missing$ + { format.bvolume output + new.block + format.number.series output + new.sentence + publisher "publisher" output.check + address output + } + { new.block + format.book.crossref output.nonnull + } + if$ + format.edition output + format.date "year" output.check + format.isbn output + format.doi output + format.url output + new.block + note output + fin.entry +} + +FUNCTION {booklet} +{ output.bibitem + format.authors output + author format.key output + new.block + format.title "title" output.check + howpublished address new.block.checkb + howpublished output + address output + format.date output + format.isbn output + format.doi output + format.url output + new.block + note output + fin.entry +} + +FUNCTION {inbook} +{ output.bibitem + author empty$ + { format.editors "author and editor" output.check + editor format.key output + } + { format.authors output.nonnull + crossref missing$ + { "author and editor" editor either.or.check } + 'skip$ + if$ + } + if$ + new.block + format.btitle "title" output.check + crossref missing$ + { format.bvolume output + format.chapter.pages "chapter and pages" output.check + new.block + format.number.series output + new.sentence + publisher "publisher" output.check + address output + } + { format.chapter.pages "chapter and pages" output.check + new.block + format.book.crossref output.nonnull + } + if$ + format.edition output + format.date "year" output.check + format.isbn output + format.doi output + format.url output + new.block + note output + fin.entry +} + +FUNCTION {incollection} +{ output.bibitem + format.authors "author" output.check + author format.key output + new.block + format.title "title" output.check + new.block + crossref missing$ + { format.in.ed.booktitle "booktitle" output.check + format.bvolume output + format.number.series output + format.chapter.pages output + new.sentence + publisher "publisher" output.check + address output + format.edition output + format.date "year" output.check + } + { format.incoll.inproc.crossref output.nonnull + format.chapter.pages output + } + if$ + format.isbn output + format.doi output + format.url output + new.block + note output + fin.entry +} + +FUNCTION {inproceedings} +{ output.bibitem + format.authors "author" output.check + author format.key output + new.block + format.title "title" output.check + new.block + crossref missing$ + { format.in.ed.booktitle "booktitle" output.check + format.bvolume output + format.number.series output + format.pages output + address empty$ + { organization publisher new.sentence.checkb + organization output + publisher output + format.date "year" output.check + } + { address output.nonnull + format.date "year" output.check + new.sentence + organization output + publisher output + } + if$ + } + { format.incoll.inproc.crossref output.nonnull + format.pages output + } + if$ + format.isbn output + format.doi output + format.url output + new.block + note output + fin.entry +} + +FUNCTION {conference} { inproceedings } + +FUNCTION {manual} +{ output.bibitem + format.authors output + author format.key output + new.block + format.btitle "title" output.check + organization address new.block.checkb + organization output + address output + format.edition output + format.date output + format.url output + new.block + note output + fin.entry +} + +FUNCTION {mastersthesis} +{ output.bibitem + format.authors "author" output.check + author format.key output + new.block + format.title "title" output.check + new.block + "Master's thesis" format.thesis.type output.nonnull + school "school" output.check + address output + format.date "year" output.check + format.url output + new.block + note output + fin.entry +} + +FUNCTION {misc} +{ output.bibitem + format.authors output + author format.key output + title howpublished new.block.checkb + format.title output + howpublished new.block.checka + howpublished output + format.date output + format.issn output + format.url output + new.block + note output + fin.entry + empty.misc.check +} + +FUNCTION {phdthesis} +{ output.bibitem + format.authors "author" output.check + author format.key output + new.block + format.btitle "title" output.check + new.block + "PhD thesis" format.thesis.type output.nonnull + school "school" output.check + address output + format.date "year" output.check + format.url output + new.block + note output + fin.entry +} + +FUNCTION {proceedings} +{ output.bibitem + format.editors output + editor format.key output + new.block + format.btitle "title" output.check + format.bvolume output + format.number.series output + address output + format.date "year" output.check + new.sentence + organization output + publisher output + format.isbn output + format.doi output + format.url output + new.block + note output + fin.entry +} + +FUNCTION {techreport} +{ output.bibitem + format.authors "author" output.check + author format.key output + new.block + format.title "title" output.check + new.block + format.tr.number output.nonnull + institution "institution" output.check + address output + format.date "year" output.check + format.url output + new.block + note output + fin.entry +} + +FUNCTION {unpublished} +{ output.bibitem + format.authors "author" output.check + author format.key output + new.block + format.title "title" output.check + new.block + note "note" output.check + format.date output + format.url output + fin.entry +} + +FUNCTION {default.type} { misc } + + +MACRO {jan} {"January"} + +MACRO {feb} {"February"} + +MACRO {mar} {"March"} + +MACRO {apr} {"April"} + +MACRO {may} {"May"} + +MACRO {jun} {"June"} + +MACRO {jul} {"July"} + +MACRO {aug} {"August"} + +MACRO {sep} {"September"} + +MACRO {oct} {"October"} + +MACRO {nov} {"November"} + +MACRO {dec} {"December"} + + + +MACRO {acmcs} {"ACM Computing Surveys"} + +MACRO {acta} {"Acta Informatica"} + +MACRO {cacm} {"Communications of the ACM"} + +MACRO {ibmjrd} {"IBM Journal of Research and Development"} + +MACRO {ibmsj} {"IBM Systems Journal"} + +MACRO {ieeese} {"IEEE Transactions on Software Engineering"} + +MACRO {ieeetc} {"IEEE Transactions on Computers"} + +MACRO {ieeetcad} + {"IEEE Transactions on Computer-Aided Design of Integrated Circuits"} + +MACRO {ipl} {"Information Processing Letters"} + +MACRO {jacm} {"Journal of the ACM"} + +MACRO {jcss} {"Journal of Computer and System Sciences"} + +MACRO {scp} {"Science of Computer Programming"} + +MACRO {sicomp} {"SIAM Journal on Computing"} + +MACRO {tocs} {"ACM Transactions on Computer Systems"} + +MACRO {tods} {"ACM Transactions on Database Systems"} + +MACRO {tog} {"ACM Transactions on Graphics"} + +MACRO {toms} {"ACM Transactions on Mathematical Software"} + +MACRO {toois} {"ACM Transactions on Office Information Systems"} + +MACRO {toplas} {"ACM Transactions on Programming Languages and Systems"} + +MACRO {tcs} {"Theoretical Computer Science"} + + +READ + +FUNCTION {sortify} +{ purify$ + "l" change.case$ +} + +INTEGERS { len } + +FUNCTION {chop.word} +{ 's := + 'len := + s #1 len substring$ = + { s len #1 + global.max$ substring$ } + 's + if$ +} + +FUNCTION {format.lab.names} +{ 's := + s #1 "{vv~}{ll}" format.name$ + s num.names$ duplicate$ + #2 > + { pop$ " et~al." * } + { #2 < + 'skip$ + { s #2 "{ff }{vv }{ll}{ jj}" format.name$ "others" = + { " et~al." * } + { " \& " * s #2 "{vv~}{ll}" format.name$ * } + if$ + } + if$ + } + if$ +} + +FUNCTION {author.key.label} +{ author empty$ + { key empty$ + { cite$ #1 #3 substring$ } + 'key + if$ + } + { author format.lab.names } + if$ +} + +FUNCTION {author.editor.key.label} +{ author empty$ + { editor empty$ + { key empty$ + { cite$ #1 #3 substring$ } + 'key + if$ + } + { editor format.lab.names } + if$ + } + { author format.lab.names } + if$ +} + +FUNCTION {author.key.organization.label} +{ author empty$ + { key empty$ + { organization empty$ + { cite$ #1 #3 substring$ } + { "The " #4 organization chop.word #3 text.prefix$ } + if$ + } + 'key + if$ + } + { author format.lab.names } + if$ +} + +FUNCTION {editor.key.organization.label} +{ editor empty$ + { key empty$ + { organization empty$ + { cite$ #1 #3 substring$ } + { "The " #4 organization chop.word #3 text.prefix$ } + if$ + } + 'key + if$ + } + { editor format.lab.names } + if$ +} + +FUNCTION {calc.short.authors} +{ type$ "book" = + type$ "inbook" = + or + 'author.editor.key.label + { type$ "proceedings" = + 'editor.key.organization.label + { type$ "manual" = + 'author.key.organization.label + 'author.key.label + if$ + } + if$ + } + if$ + 'short.list := +} + +FUNCTION {calc.label} +{ calc.short.authors + short.list + "(" + * + year duplicate$ empty$ + short.list key field.or.null = or + { pop$ "" } + 'skip$ + if$ + * + 'label := +} + +FUNCTION {sort.format.names} +{ 's := + #1 'nameptr := + "" + s num.names$ 'numnames := + numnames 'namesleft := + { namesleft #0 > } + { + s nameptr "{vv{ } }{ll{ }}{ ff{ }}{ jj{ }}" format.name$ 't := + nameptr #1 > + { + " " * + namesleft #1 = t "others" = and + { "zzzzz" * } + { numnames #2 > nameptr #2 = and + { "zz" * year field.or.null * " " * } + 'skip$ + if$ + t sortify * + } + if$ + } + { t sortify * } + if$ + nameptr #1 + 'nameptr := + namesleft #1 - 'namesleft := + } + while$ +} + +FUNCTION {sort.format.title} +{ 't := + "A " #2 + "An " #3 + "The " #4 t chop.word + chop.word + chop.word + sortify + #1 global.max$ substring$ +} + +FUNCTION {author.sort} +{ author empty$ + { key empty$ + { "to sort, need author or key in " cite$ * warning$ + "" + } + { key sortify } + if$ + } + { author sort.format.names } + if$ +} + +FUNCTION {author.editor.sort} +{ author empty$ + { editor empty$ + { key empty$ + { "to sort, need author, editor, or key in " cite$ * warning$ + "" + } + { key sortify } + if$ + } + { editor sort.format.names } + if$ + } + { author sort.format.names } + if$ +} + +FUNCTION {author.organization.sort} +{ author empty$ + { organization empty$ + { key empty$ + { "to sort, need author, organization, or key in " cite$ * warning$ + "" + } + { key sortify } + if$ + } + { "The " #4 organization chop.word sortify } + if$ + } + { author sort.format.names } + if$ +} + +FUNCTION {editor.organization.sort} +{ editor empty$ + { organization empty$ + { key empty$ + { "to sort, need editor, organization, or key in " cite$ * warning$ + "" + } + { key sortify } + if$ + } + { "The " #4 organization chop.word sortify } + if$ + } + { editor sort.format.names } + if$ +} + + +FUNCTION {presort} +{ calc.label + label sortify + " " + * + type$ "book" = + type$ "inbook" = + or + 'author.editor.sort + { type$ "proceedings" = + 'editor.organization.sort + { type$ "manual" = + 'author.organization.sort + 'author.sort + if$ + } + if$ + } + if$ + " " + * + year field.or.null sortify + * + " " + * + cite$ + * + #1 entry.max$ substring$ + 'sort.label := + sort.label * + #1 entry.max$ substring$ + 'sort.key$ := +} + +ITERATE {presort} + +SORT + +STRINGS { longest.label last.label next.extra } + +INTEGERS { longest.label.width last.extra.num number.label } + +FUNCTION {initialize.longest.label} +{ "" 'longest.label := + #0 int.to.chr$ 'last.label := + "" 'next.extra := + #0 'longest.label.width := + #0 'last.extra.num := + #0 'number.label := +} + +FUNCTION {forward.pass} +{ last.label label = + { last.extra.num #1 + 'last.extra.num := + last.extra.num int.to.chr$ 'extra.label := + } + { "a" chr.to.int$ 'last.extra.num := + "" 'extra.label := + label 'last.label := + } + if$ + number.label #1 + 'number.label := +} + +FUNCTION {reverse.pass} +{ next.extra "b" = + { "a" 'extra.label := } + 'skip$ + if$ + extra.label 'next.extra := + extra.label + duplicate$ empty$ + 'skip$ + { "{\natexlab{" swap$ * "}}" * } + if$ + 'extra.label := + label extra.label * 'label := +} + +EXECUTE {initialize.longest.label} + +ITERATE {forward.pass} + +REVERSE {reverse.pass} + +FUNCTION {bib.sort.order} +{ sort.label 'sort.key$ := +} + +ITERATE {bib.sort.order} + +SORT + +FUNCTION {begin.bib} +{ preamble$ empty$ + 'skip$ + { preamble$ write$ newline$ } + if$ + "\begin{thebibliography}{" number.label int.to.str$ * "}" * + write$ newline$ + "\providecommand{\natexlab}[1]{#1}" + write$ newline$ + "\providecommand{\url}[1]{\texttt{#1}}" + write$ newline$ + "\expandafter\ifx\csname urlstyle\endcsname\relax" + write$ newline$ + " \providecommand{\doi}[1]{doi: #1}\else" + write$ newline$ + " \providecommand{\doi}{doi: \begingroup \urlstyle{rm}\Url}\fi" + write$ newline$ +} + +EXECUTE {begin.bib} + +EXECUTE {init.state.consts} + +ITERATE {call.type$} + +FUNCTION {end.bib} +{ newline$ + "\end{thebibliography}" write$ newline$ +} + +EXECUTE {end.bib} diff --git a/latex_templates/ICLR2022/iclr2022_conference.sty b/latex_templates/ICLR2022/iclr2022_conference.sty new file mode 100644 index 0000000000000000000000000000000000000000..03c8b38954cb906fc1526e692b6757c5fda87a98 --- /dev/null +++ b/latex_templates/ICLR2022/iclr2022_conference.sty @@ -0,0 +1,245 @@ +%%%% ICLR Macros (LaTex) +%%%% Adapted by Hugo Larochelle from the NIPS stylefile Macros +%%%% Style File +%%%% Dec 12, 1990 Rev Aug 14, 1991; Sept, 1995; April, 1997; April, 1999; October 2014 + +% This file can be used with Latex2e whether running in main mode, or +% 2.09 compatibility mode. +% +% If using main mode, you need to include the commands +% \documentclass{article} +% \usepackage{iclr14submit_e,times} +% + +% Change the overall width of the page. If these parameters are +% changed, they will require corresponding changes in the +% maketitle section. +% +\usepackage{eso-pic} % used by \AddToShipoutPicture +\RequirePackage{fancyhdr} +\RequirePackage{natbib} + +% modification to natbib citations +\setcitestyle{authoryear,round,citesep={;},aysep={,},yysep={;}} + +\renewcommand{\topfraction}{0.95} % let figure take up nearly whole page +\renewcommand{\textfraction}{0.05} % let figure take up nearly whole page + +% Define iclrfinal, set to true if iclrfinalcopy is defined +\newif\ificlrfinal +\iclrfinalfalse +\def\iclrfinalcopy{\iclrfinaltrue} +\font\iclrtenhv = phvb at 8pt + +% Specify the dimensions of each page + +\setlength{\paperheight}{11in} +\setlength{\paperwidth}{8.5in} + + +\oddsidemargin .5in % Note \oddsidemargin = \evensidemargin +\evensidemargin .5in +\marginparwidth 0.07 true in +%\marginparwidth 0.75 true in +%\topmargin 0 true pt % Nominal distance from top of page to top of +%\topmargin 0.125in +\topmargin -0.625in +\addtolength{\headsep}{0.25in} +\textheight 9.0 true in % Height of text (including footnotes & figures) +\textwidth 5.5 true in % Width of text line. +\widowpenalty=10000 +\clubpenalty=10000 + +% \thispagestyle{empty} \pagestyle{empty} +\flushbottom \sloppy + +% We're never going to need a table of contents, so just flush it to +% save space --- suggested by drstrip@sandia-2 +\def\addcontentsline#1#2#3{} + +% Title stuff, taken from deproc. +\def\maketitle{\par +\begingroup + \def\thefootnote{\fnsymbol{footnote}} + \def\@makefnmark{\hbox to 0pt{$^{\@thefnmark}$\hss}} % for perfect author + % name centering +% The footnote-mark was overlapping the footnote-text, +% added the following to fix this problem (MK) + \long\def\@makefntext##1{\parindent 1em\noindent + \hbox to1.8em{\hss $\m@th ^{\@thefnmark}$}##1} + \@maketitle \@thanks +\endgroup +\setcounter{footnote}{0} +\let\maketitle\relax \let\@maketitle\relax +\gdef\@thanks{}\gdef\@author{}\gdef\@title{}\let\thanks\relax} + +% The toptitlebar has been raised to top-justify the first page + +\usepackage{fancyhdr} +\pagestyle{fancy} +\fancyhead{} + +% Title (includes both anonimized and non-anonimized versions) +\def\@maketitle{\vbox{\hsize\textwidth +%\linewidth\hsize \vskip 0.1in \toptitlebar \centering +{\LARGE\sc \@title\par} +%\bottomtitlebar % \vskip 0.1in % minus +\ificlrfinal + \lhead{Published as a conference paper at ICLR 2022} + \def\And{\end{tabular}\hfil\linebreak[0]\hfil + \begin{tabular}[t]{l}\bf\rule{\z@}{24pt}\ignorespaces}% + \def\AND{\end{tabular}\hfil\linebreak[4]\hfil + \begin{tabular}[t]{l}\bf\rule{\z@}{24pt}\ignorespaces}% + \begin{tabular}[t]{l}\bf\rule{\z@}{24pt}\@author\end{tabular}% +\else + \lhead{Under review as a conference paper at ICLR 2022} + \def\And{\end{tabular}\hfil\linebreak[0]\hfil + \begin{tabular}[t]{l}\bf\rule{\z@}{24pt}\ignorespaces}% + \def\AND{\end{tabular}\hfil\linebreak[4]\hfil + \begin{tabular}[t]{l}\bf\rule{\z@}{24pt}\ignorespaces}% + \begin{tabular}[t]{l}\bf\rule{\z@}{24pt}Anonymous authors\\Paper under double-blind review\end{tabular}% +\fi +\vskip 0.3in minus 0.1in}} + +\renewenvironment{abstract}{\vskip.075in\centerline{\large\sc +Abstract}\vspace{0.5ex}\begin{quote}}{\par\end{quote}\vskip 1ex} + +% sections with less space +\def\section{\@startsection {section}{1}{\z@}{-2.0ex plus + -0.5ex minus -.2ex}{1.5ex plus 0.3ex +minus0.2ex}{\large\sc\raggedright}} + +\def\subsection{\@startsection{subsection}{2}{\z@}{-1.8ex plus +-0.5ex minus -.2ex}{0.8ex plus .2ex}{\normalsize\sc\raggedright}} +\def\subsubsection{\@startsection{subsubsection}{3}{\z@}{-1.5ex +plus -0.5ex minus -.2ex}{0.5ex plus +.2ex}{\normalsize\sc\raggedright}} +\def\paragraph{\@startsection{paragraph}{4}{\z@}{1.5ex plus +0.5ex minus .2ex}{-1em}{\normalsize\bf}} +\def\subparagraph{\@startsection{subparagraph}{5}{\z@}{1.5ex plus + 0.5ex minus .2ex}{-1em}{\normalsize\sc}} +\def\subsubsubsection{\vskip +5pt{\noindent\normalsize\rm\raggedright}} + + +% Footnotes +\footnotesep 6.65pt % +\skip\footins 9pt plus 4pt minus 2pt +\def\footnoterule{\kern-3pt \hrule width 12pc \kern 2.6pt } +\setcounter{footnote}{0} + +% Lists and paragraphs +\parindent 0pt +\topsep 4pt plus 1pt minus 2pt +\partopsep 1pt plus 0.5pt minus 0.5pt +\itemsep 2pt plus 1pt minus 0.5pt +\parsep 2pt plus 1pt minus 0.5pt +\parskip .5pc + + +%\leftmargin2em +\leftmargin3pc +\leftmargini\leftmargin \leftmarginii 2em +\leftmarginiii 1.5em \leftmarginiv 1.0em \leftmarginv .5em + +%\labelsep \labelsep 5pt + +\def\@listi{\leftmargin\leftmargini} +\def\@listii{\leftmargin\leftmarginii + \labelwidth\leftmarginii\advance\labelwidth-\labelsep + \topsep 2pt plus 1pt minus 0.5pt + \parsep 1pt plus 0.5pt minus 0.5pt + \itemsep \parsep} +\def\@listiii{\leftmargin\leftmarginiii + \labelwidth\leftmarginiii\advance\labelwidth-\labelsep + \topsep 1pt plus 0.5pt minus 0.5pt + \parsep \z@ \partopsep 0.5pt plus 0pt minus 0.5pt + \itemsep \topsep} +\def\@listiv{\leftmargin\leftmarginiv + \labelwidth\leftmarginiv\advance\labelwidth-\labelsep} +\def\@listv{\leftmargin\leftmarginv + \labelwidth\leftmarginv\advance\labelwidth-\labelsep} +\def\@listvi{\leftmargin\leftmarginvi + \labelwidth\leftmarginvi\advance\labelwidth-\labelsep} + +\abovedisplayskip 7pt plus2pt minus5pt% +\belowdisplayskip \abovedisplayskip +\abovedisplayshortskip 0pt plus3pt% +\belowdisplayshortskip 4pt plus3pt minus3pt% + +% Less leading in most fonts (due to the narrow columns) +% The choices were between 1-pt and 1.5-pt leading +%\def\@normalsize{\@setsize\normalsize{11pt}\xpt\@xpt} % got rid of @ (MK) +\def\normalsize{\@setsize\normalsize{11pt}\xpt\@xpt} +\def\small{\@setsize\small{10pt}\ixpt\@ixpt} +\def\footnotesize{\@setsize\footnotesize{10pt}\ixpt\@ixpt} +\def\scriptsize{\@setsize\scriptsize{8pt}\viipt\@viipt} +\def\tiny{\@setsize\tiny{7pt}\vipt\@vipt} +\def\large{\@setsize\large{14pt}\xiipt\@xiipt} +\def\Large{\@setsize\Large{16pt}\xivpt\@xivpt} +\def\LARGE{\@setsize\LARGE{20pt}\xviipt\@xviipt} +\def\huge{\@setsize\huge{23pt}\xxpt\@xxpt} +\def\Huge{\@setsize\Huge{28pt}\xxvpt\@xxvpt} + +\def\toptitlebar{\hrule height4pt\vskip .25in\vskip-\parskip} + +\def\bottomtitlebar{\vskip .29in\vskip-\parskip\hrule height1pt\vskip +.09in} % +%Reduced second vskip to compensate for adding the strut in \@author + + +%% % Vertical Ruler +%% % This code is, largely, from the CVPR 2010 conference style file +%% % ----- define vruler +%% \makeatletter +%% \newbox\iclrrulerbox +%% \newcount\iclrrulercount +%% \newdimen\iclrruleroffset +%% \newdimen\cv@lineheight +%% \newdimen\cv@boxheight +%% \newbox\cv@tmpbox +%% \newcount\cv@refno +%% \newcount\cv@tot +%% % NUMBER with left flushed zeros \fillzeros[] +%% \newcount\cv@tmpc@ \newcount\cv@tmpc +%% \def\fillzeros[#1]#2{\cv@tmpc@=#2\relax\ifnum\cv@tmpc@<0\cv@tmpc@=-\cv@tmpc@\fi +%% \cv@tmpc=1 % +%% \loop\ifnum\cv@tmpc@<10 \else \divide\cv@tmpc@ by 10 \advance\cv@tmpc by 1 \fi +%% \ifnum\cv@tmpc@=10\relax\cv@tmpc@=11\relax\fi \ifnum\cv@tmpc@>10 \repeat +%% \ifnum#2<0\advance\cv@tmpc1\relax-\fi +%% \loop\ifnum\cv@tmpc<#1\relax0\advance\cv@tmpc1\relax\fi \ifnum\cv@tmpc<#1 \repeat +%% \cv@tmpc@=#2\relax\ifnum\cv@tmpc@<0\cv@tmpc@=-\cv@tmpc@\fi \relax\the\cv@tmpc@}% +%% % \makevruler[][][][][] +%% \def\makevruler[#1][#2][#3][#4][#5]{\begingroup\offinterlineskip +%% \textheight=#5\vbadness=10000\vfuzz=120ex\overfullrule=0pt% +%% \global\setbox\iclrrulerbox=\vbox to \textheight{% +%% {\parskip=0pt\hfuzz=150em\cv@boxheight=\textheight +%% \cv@lineheight=#1\global\iclrrulercount=#2% +%% \cv@tot\cv@boxheight\divide\cv@tot\cv@lineheight\advance\cv@tot2% +%% \cv@refno1\vskip-\cv@lineheight\vskip1ex% +%% \loop\setbox\cv@tmpbox=\hbox to0cm{{\iclrtenhv\hfil\fillzeros[#4]\iclrrulercount}}% +%% \ht\cv@tmpbox\cv@lineheight\dp\cv@tmpbox0pt\box\cv@tmpbox\break +%% \advance\cv@refno1\global\advance\iclrrulercount#3\relax +%% \ifnum\cv@refno<\cv@tot\repeat}}\endgroup}% +%% \makeatother +%% % ----- end of vruler + +%% % \makevruler[][][][][] +%% \def\iclrruler#1{\makevruler[12pt][#1][1][3][0.993\textheight]\usebox{\iclrrulerbox}} +%% \AddToShipoutPicture{% +%% \ificlrfinal\else +%% \iclrruleroffset=\textheight +%% \advance\iclrruleroffset by -3.7pt +%% \color[rgb]{.7,.7,.7} +%% \AtTextUpperLeft{% +%% \put(\LenToUnit{-35pt},\LenToUnit{-\iclrruleroffset}){%left ruler +%% \iclrruler{\iclrrulercount}} +%% } +%% \fi +%% } +%%% To add a vertical bar on the side +%\AddToShipoutPicture{ +%\AtTextLowerLeft{ +%\hspace*{-1.8cm} +%\colorbox[rgb]{0.7,0.7,0.7}{\small \parbox[b][\textheight]{0.1cm}{}}} +%} diff --git a/latex_templates/ICLR2022/introduction.tex b/latex_templates/ICLR2022/introduction.tex new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/latex_templates/ICLR2022/math_commands.tex b/latex_templates/ICLR2022/math_commands.tex new file mode 100644 index 0000000000000000000000000000000000000000..0668f931945175ca8535db25cc27fa603920cc3c --- /dev/null +++ b/latex_templates/ICLR2022/math_commands.tex @@ -0,0 +1,508 @@ +%%%%% NEW MATH DEFINITIONS %%%%% + +\usepackage{amsmath,amsfonts,bm} + +% Mark sections of captions for referring to divisions of figures +\newcommand{\figleft}{{\em (Left)}} +\newcommand{\figcenter}{{\em (Center)}} +\newcommand{\figright}{{\em (Right)}} +\newcommand{\figtop}{{\em (Top)}} +\newcommand{\figbottom}{{\em (Bottom)}} +\newcommand{\captiona}{{\em (a)}} +\newcommand{\captionb}{{\em (b)}} +\newcommand{\captionc}{{\em (c)}} +\newcommand{\captiond}{{\em (d)}} + +% Highlight a newly defined term +\newcommand{\newterm}[1]{{\bf #1}} + + +% Figure reference, lower-case. +\def\figref#1{figure~\ref{#1}} +% Figure reference, capital. For start of sentence +\def\Figref#1{Figure~\ref{#1}} +\def\twofigref#1#2{figures \ref{#1} and \ref{#2}} +\def\quadfigref#1#2#3#4{figures \ref{#1}, \ref{#2}, \ref{#3} and \ref{#4}} +% Section reference, lower-case. +\def\secref#1{section~\ref{#1}} +% Section reference, capital. +\def\Secref#1{Section~\ref{#1}} +% Reference to two sections. +\def\twosecrefs#1#2{sections \ref{#1} and \ref{#2}} +% Reference to three sections. +\def\secrefs#1#2#3{sections \ref{#1}, \ref{#2} and \ref{#3}} +% Reference to an equation, lower-case. +\def\eqref#1{equation~\ref{#1}} +% Reference to an equation, upper case +\def\Eqref#1{Equation~\ref{#1}} +% A raw reference to an equation---avoid using if possible +\def\plaineqref#1{\ref{#1}} +% Reference to a chapter, lower-case. +\def\chapref#1{chapter~\ref{#1}} +% Reference to an equation, upper case. +\def\Chapref#1{Chapter~\ref{#1}} +% Reference to a range of chapters +\def\rangechapref#1#2{chapters\ref{#1}--\ref{#2}} +% Reference to an algorithm, lower-case. +\def\algref#1{algorithm~\ref{#1}} +% Reference to an algorithm, upper case. +\def\Algref#1{Algorithm~\ref{#1}} +\def\twoalgref#1#2{algorithms \ref{#1} and \ref{#2}} +\def\Twoalgref#1#2{Algorithms \ref{#1} and \ref{#2}} +% Reference to a part, lower case +\def\partref#1{part~\ref{#1}} +% Reference to a part, upper case +\def\Partref#1{Part~\ref{#1}} +\def\twopartref#1#2{parts \ref{#1} and \ref{#2}} + +\def\ceil#1{\lceil #1 \rceil} +\def\floor#1{\lfloor #1 \rfloor} +\def\1{\bm{1}} +\newcommand{\train}{\mathcal{D}} +\newcommand{\valid}{\mathcal{D_{\mathrm{valid}}}} +\newcommand{\test}{\mathcal{D_{\mathrm{test}}}} + +\def\eps{{\epsilon}} + + +% Random variables +\def\reta{{\textnormal{$\eta$}}} +\def\ra{{\textnormal{a}}} +\def\rb{{\textnormal{b}}} +\def\rc{{\textnormal{c}}} +\def\rd{{\textnormal{d}}} +\def\re{{\textnormal{e}}} +\def\rf{{\textnormal{f}}} +\def\rg{{\textnormal{g}}} +\def\rh{{\textnormal{h}}} +\def\ri{{\textnormal{i}}} +\def\rj{{\textnormal{j}}} +\def\rk{{\textnormal{k}}} +\def\rl{{\textnormal{l}}} +% rm is already a command, just don't name any random variables m +\def\rn{{\textnormal{n}}} +\def\ro{{\textnormal{o}}} +\def\rp{{\textnormal{p}}} +\def\rq{{\textnormal{q}}} +\def\rr{{\textnormal{r}}} +\def\rs{{\textnormal{s}}} +\def\rt{{\textnormal{t}}} +\def\ru{{\textnormal{u}}} +\def\rv{{\textnormal{v}}} +\def\rw{{\textnormal{w}}} +\def\rx{{\textnormal{x}}} +\def\ry{{\textnormal{y}}} +\def\rz{{\textnormal{z}}} + +% Random vectors +\def\rvepsilon{{\mathbf{\epsilon}}} +\def\rvtheta{{\mathbf{\theta}}} +\def\rva{{\mathbf{a}}} +\def\rvb{{\mathbf{b}}} +\def\rvc{{\mathbf{c}}} +\def\rvd{{\mathbf{d}}} +\def\rve{{\mathbf{e}}} +\def\rvf{{\mathbf{f}}} +\def\rvg{{\mathbf{g}}} +\def\rvh{{\mathbf{h}}} +\def\rvu{{\mathbf{i}}} +\def\rvj{{\mathbf{j}}} +\def\rvk{{\mathbf{k}}} +\def\rvl{{\mathbf{l}}} +\def\rvm{{\mathbf{m}}} +\def\rvn{{\mathbf{n}}} +\def\rvo{{\mathbf{o}}} +\def\rvp{{\mathbf{p}}} +\def\rvq{{\mathbf{q}}} +\def\rvr{{\mathbf{r}}} +\def\rvs{{\mathbf{s}}} +\def\rvt{{\mathbf{t}}} +\def\rvu{{\mathbf{u}}} +\def\rvv{{\mathbf{v}}} +\def\rvw{{\mathbf{w}}} +\def\rvx{{\mathbf{x}}} +\def\rvy{{\mathbf{y}}} +\def\rvz{{\mathbf{z}}} + +% Elements of random vectors +\def\erva{{\textnormal{a}}} +\def\ervb{{\textnormal{b}}} +\def\ervc{{\textnormal{c}}} +\def\ervd{{\textnormal{d}}} +\def\erve{{\textnormal{e}}} +\def\ervf{{\textnormal{f}}} +\def\ervg{{\textnormal{g}}} +\def\ervh{{\textnormal{h}}} +\def\ervi{{\textnormal{i}}} +\def\ervj{{\textnormal{j}}} +\def\ervk{{\textnormal{k}}} +\def\ervl{{\textnormal{l}}} +\def\ervm{{\textnormal{m}}} +\def\ervn{{\textnormal{n}}} +\def\ervo{{\textnormal{o}}} +\def\ervp{{\textnormal{p}}} +\def\ervq{{\textnormal{q}}} +\def\ervr{{\textnormal{r}}} +\def\ervs{{\textnormal{s}}} +\def\ervt{{\textnormal{t}}} +\def\ervu{{\textnormal{u}}} +\def\ervv{{\textnormal{v}}} +\def\ervw{{\textnormal{w}}} +\def\ervx{{\textnormal{x}}} +\def\ervy{{\textnormal{y}}} +\def\ervz{{\textnormal{z}}} + +% Random matrices +\def\rmA{{\mathbf{A}}} +\def\rmB{{\mathbf{B}}} +\def\rmC{{\mathbf{C}}} +\def\rmD{{\mathbf{D}}} +\def\rmE{{\mathbf{E}}} +\def\rmF{{\mathbf{F}}} +\def\rmG{{\mathbf{G}}} +\def\rmH{{\mathbf{H}}} +\def\rmI{{\mathbf{I}}} +\def\rmJ{{\mathbf{J}}} +\def\rmK{{\mathbf{K}}} +\def\rmL{{\mathbf{L}}} +\def\rmM{{\mathbf{M}}} +\def\rmN{{\mathbf{N}}} +\def\rmO{{\mathbf{O}}} +\def\rmP{{\mathbf{P}}} +\def\rmQ{{\mathbf{Q}}} +\def\rmR{{\mathbf{R}}} +\def\rmS{{\mathbf{S}}} +\def\rmT{{\mathbf{T}}} +\def\rmU{{\mathbf{U}}} +\def\rmV{{\mathbf{V}}} +\def\rmW{{\mathbf{W}}} +\def\rmX{{\mathbf{X}}} +\def\rmY{{\mathbf{Y}}} +\def\rmZ{{\mathbf{Z}}} + +% Elements of random matrices +\def\ermA{{\textnormal{A}}} +\def\ermB{{\textnormal{B}}} +\def\ermC{{\textnormal{C}}} +\def\ermD{{\textnormal{D}}} +\def\ermE{{\textnormal{E}}} +\def\ermF{{\textnormal{F}}} +\def\ermG{{\textnormal{G}}} +\def\ermH{{\textnormal{H}}} +\def\ermI{{\textnormal{I}}} +\def\ermJ{{\textnormal{J}}} +\def\ermK{{\textnormal{K}}} +\def\ermL{{\textnormal{L}}} +\def\ermM{{\textnormal{M}}} +\def\ermN{{\textnormal{N}}} +\def\ermO{{\textnormal{O}}} +\def\ermP{{\textnormal{P}}} +\def\ermQ{{\textnormal{Q}}} +\def\ermR{{\textnormal{R}}} +\def\ermS{{\textnormal{S}}} +\def\ermT{{\textnormal{T}}} +\def\ermU{{\textnormal{U}}} +\def\ermV{{\textnormal{V}}} +\def\ermW{{\textnormal{W}}} +\def\ermX{{\textnormal{X}}} +\def\ermY{{\textnormal{Y}}} +\def\ermZ{{\textnormal{Z}}} + +% Vectors +\def\vzero{{\bm{0}}} +\def\vone{{\bm{1}}} +\def\vmu{{\bm{\mu}}} +\def\vtheta{{\bm{\theta}}} +\def\va{{\bm{a}}} +\def\vb{{\bm{b}}} +\def\vc{{\bm{c}}} +\def\vd{{\bm{d}}} +\def\ve{{\bm{e}}} +\def\vf{{\bm{f}}} +\def\vg{{\bm{g}}} +\def\vh{{\bm{h}}} +\def\vi{{\bm{i}}} +\def\vj{{\bm{j}}} +\def\vk{{\bm{k}}} +\def\vl{{\bm{l}}} +\def\vm{{\bm{m}}} +\def\vn{{\bm{n}}} +\def\vo{{\bm{o}}} +\def\vp{{\bm{p}}} +\def\vq{{\bm{q}}} +\def\vr{{\bm{r}}} +\def\vs{{\bm{s}}} +\def\vt{{\bm{t}}} +\def\vu{{\bm{u}}} +\def\vv{{\bm{v}}} +\def\vw{{\bm{w}}} +\def\vx{{\bm{x}}} +\def\vy{{\bm{y}}} +\def\vz{{\bm{z}}} + +% Elements of vectors +\def\evalpha{{\alpha}} +\def\evbeta{{\beta}} +\def\evepsilon{{\epsilon}} +\def\evlambda{{\lambda}} +\def\evomega{{\omega}} +\def\evmu{{\mu}} +\def\evpsi{{\psi}} +\def\evsigma{{\sigma}} +\def\evtheta{{\theta}} +\def\eva{{a}} +\def\evb{{b}} +\def\evc{{c}} +\def\evd{{d}} +\def\eve{{e}} +\def\evf{{f}} +\def\evg{{g}} +\def\evh{{h}} +\def\evi{{i}} +\def\evj{{j}} +\def\evk{{k}} +\def\evl{{l}} +\def\evm{{m}} +\def\evn{{n}} +\def\evo{{o}} +\def\evp{{p}} +\def\evq{{q}} +\def\evr{{r}} +\def\evs{{s}} +\def\evt{{t}} +\def\evu{{u}} +\def\evv{{v}} +\def\evw{{w}} +\def\evx{{x}} +\def\evy{{y}} +\def\evz{{z}} + +% Matrix +\def\mA{{\bm{A}}} +\def\mB{{\bm{B}}} +\def\mC{{\bm{C}}} +\def\mD{{\bm{D}}} +\def\mE{{\bm{E}}} +\def\mF{{\bm{F}}} +\def\mG{{\bm{G}}} +\def\mH{{\bm{H}}} +\def\mI{{\bm{I}}} +\def\mJ{{\bm{J}}} +\def\mK{{\bm{K}}} +\def\mL{{\bm{L}}} +\def\mM{{\bm{M}}} +\def\mN{{\bm{N}}} +\def\mO{{\bm{O}}} +\def\mP{{\bm{P}}} +\def\mQ{{\bm{Q}}} +\def\mR{{\bm{R}}} +\def\mS{{\bm{S}}} +\def\mT{{\bm{T}}} +\def\mU{{\bm{U}}} +\def\mV{{\bm{V}}} +\def\mW{{\bm{W}}} +\def\mX{{\bm{X}}} +\def\mY{{\bm{Y}}} +\def\mZ{{\bm{Z}}} +\def\mBeta{{\bm{\beta}}} +\def\mPhi{{\bm{\Phi}}} +\def\mLambda{{\bm{\Lambda}}} +\def\mSigma{{\bm{\Sigma}}} + +% Tensor +\DeclareMathAlphabet{\mathsfit}{\encodingdefault}{\sfdefault}{m}{sl} +\SetMathAlphabet{\mathsfit}{bold}{\encodingdefault}{\sfdefault}{bx}{n} +\newcommand{\tens}[1]{\bm{\mathsfit{#1}}} +\def\tA{{\tens{A}}} +\def\tB{{\tens{B}}} +\def\tC{{\tens{C}}} +\def\tD{{\tens{D}}} +\def\tE{{\tens{E}}} +\def\tF{{\tens{F}}} +\def\tG{{\tens{G}}} +\def\tH{{\tens{H}}} +\def\tI{{\tens{I}}} +\def\tJ{{\tens{J}}} +\def\tK{{\tens{K}}} +\def\tL{{\tens{L}}} +\def\tM{{\tens{M}}} +\def\tN{{\tens{N}}} +\def\tO{{\tens{O}}} +\def\tP{{\tens{P}}} +\def\tQ{{\tens{Q}}} +\def\tR{{\tens{R}}} +\def\tS{{\tens{S}}} +\def\tT{{\tens{T}}} +\def\tU{{\tens{U}}} +\def\tV{{\tens{V}}} +\def\tW{{\tens{W}}} +\def\tX{{\tens{X}}} +\def\tY{{\tens{Y}}} +\def\tZ{{\tens{Z}}} + + +% Graph +\def\gA{{\mathcal{A}}} +\def\gB{{\mathcal{B}}} +\def\gC{{\mathcal{C}}} +\def\gD{{\mathcal{D}}} +\def\gE{{\mathcal{E}}} +\def\gF{{\mathcal{F}}} +\def\gG{{\mathcal{G}}} +\def\gH{{\mathcal{H}}} +\def\gI{{\mathcal{I}}} +\def\gJ{{\mathcal{J}}} +\def\gK{{\mathcal{K}}} +\def\gL{{\mathcal{L}}} +\def\gM{{\mathcal{M}}} +\def\gN{{\mathcal{N}}} +\def\gO{{\mathcal{O}}} +\def\gP{{\mathcal{P}}} +\def\gQ{{\mathcal{Q}}} +\def\gR{{\mathcal{R}}} +\def\gS{{\mathcal{S}}} +\def\gT{{\mathcal{T}}} +\def\gU{{\mathcal{U}}} +\def\gV{{\mathcal{V}}} +\def\gW{{\mathcal{W}}} +\def\gX{{\mathcal{X}}} +\def\gY{{\mathcal{Y}}} +\def\gZ{{\mathcal{Z}}} + +% Sets +\def\sA{{\mathbb{A}}} +\def\sB{{\mathbb{B}}} +\def\sC{{\mathbb{C}}} +\def\sD{{\mathbb{D}}} +% Don't use a set called E, because this would be the same as our symbol +% for expectation. +\def\sF{{\mathbb{F}}} +\def\sG{{\mathbb{G}}} +\def\sH{{\mathbb{H}}} +\def\sI{{\mathbb{I}}} +\def\sJ{{\mathbb{J}}} +\def\sK{{\mathbb{K}}} +\def\sL{{\mathbb{L}}} +\def\sM{{\mathbb{M}}} +\def\sN{{\mathbb{N}}} +\def\sO{{\mathbb{O}}} +\def\sP{{\mathbb{P}}} +\def\sQ{{\mathbb{Q}}} +\def\sR{{\mathbb{R}}} +\def\sS{{\mathbb{S}}} +\def\sT{{\mathbb{T}}} +\def\sU{{\mathbb{U}}} +\def\sV{{\mathbb{V}}} +\def\sW{{\mathbb{W}}} +\def\sX{{\mathbb{X}}} +\def\sY{{\mathbb{Y}}} +\def\sZ{{\mathbb{Z}}} + +% Entries of a matrix +\def\emLambda{{\Lambda}} +\def\emA{{A}} +\def\emB{{B}} +\def\emC{{C}} +\def\emD{{D}} +\def\emE{{E}} +\def\emF{{F}} +\def\emG{{G}} +\def\emH{{H}} +\def\emI{{I}} +\def\emJ{{J}} +\def\emK{{K}} +\def\emL{{L}} +\def\emM{{M}} +\def\emN{{N}} +\def\emO{{O}} +\def\emP{{P}} +\def\emQ{{Q}} +\def\emR{{R}} +\def\emS{{S}} +\def\emT{{T}} +\def\emU{{U}} +\def\emV{{V}} +\def\emW{{W}} +\def\emX{{X}} +\def\emY{{Y}} +\def\emZ{{Z}} +\def\emSigma{{\Sigma}} + +% entries of a tensor +% Same font as tensor, without \bm wrapper +\newcommand{\etens}[1]{\mathsfit{#1}} +\def\etLambda{{\etens{\Lambda}}} +\def\etA{{\etens{A}}} +\def\etB{{\etens{B}}} +\def\etC{{\etens{C}}} +\def\etD{{\etens{D}}} +\def\etE{{\etens{E}}} +\def\etF{{\etens{F}}} +\def\etG{{\etens{G}}} +\def\etH{{\etens{H}}} +\def\etI{{\etens{I}}} +\def\etJ{{\etens{J}}} +\def\etK{{\etens{K}}} +\def\etL{{\etens{L}}} +\def\etM{{\etens{M}}} +\def\etN{{\etens{N}}} +\def\etO{{\etens{O}}} +\def\etP{{\etens{P}}} +\def\etQ{{\etens{Q}}} +\def\etR{{\etens{R}}} +\def\etS{{\etens{S}}} +\def\etT{{\etens{T}}} +\def\etU{{\etens{U}}} +\def\etV{{\etens{V}}} +\def\etW{{\etens{W}}} +\def\etX{{\etens{X}}} +\def\etY{{\etens{Y}}} +\def\etZ{{\etens{Z}}} + +% The true underlying data generating distribution +\newcommand{\pdata}{p_{\rm{data}}} +% The empirical distribution defined by the training set +\newcommand{\ptrain}{\hat{p}_{\rm{data}}} +\newcommand{\Ptrain}{\hat{P}_{\rm{data}}} +% The model distribution +\newcommand{\pmodel}{p_{\rm{model}}} +\newcommand{\Pmodel}{P_{\rm{model}}} +\newcommand{\ptildemodel}{\tilde{p}_{\rm{model}}} +% Stochastic autoencoder distributions +\newcommand{\pencode}{p_{\rm{encoder}}} +\newcommand{\pdecode}{p_{\rm{decoder}}} +\newcommand{\precons}{p_{\rm{reconstruct}}} + +\newcommand{\laplace}{\mathrm{Laplace}} % Laplace distribution + +\newcommand{\E}{\mathbb{E}} +\newcommand{\Ls}{\mathcal{L}} +\newcommand{\R}{\mathbb{R}} +\newcommand{\emp}{\tilde{p}} +\newcommand{\lr}{\alpha} +\newcommand{\reg}{\lambda} +\newcommand{\rect}{\mathrm{rectifier}} +\newcommand{\softmax}{\mathrm{softmax}} +\newcommand{\sigmoid}{\sigma} +\newcommand{\softplus}{\zeta} +\newcommand{\KL}{D_{\mathrm{KL}}} +\newcommand{\Var}{\mathrm{Var}} +\newcommand{\standarderror}{\mathrm{SE}} +\newcommand{\Cov}{\mathrm{Cov}} +% Wolfram Mathworld says $L^2$ is for function spaces and $\ell^2$ is for vectors +% But then they seem to use $L^2$ for vectors throughout the site, and so does +% wikipedia. +\newcommand{\normlzero}{L^0} +\newcommand{\normlone}{L^1} +\newcommand{\normltwo}{L^2} +\newcommand{\normlp}{L^p} +\newcommand{\normmax}{L^\infty} + +\newcommand{\parents}{Pa} % See usage in notation.tex. Chosen to match Daphne's book. + +\DeclareMathOperator*{\argmax}{arg\,max} +\DeclareMathOperator*{\argmin}{arg\,min} + +\DeclareMathOperator{\sign}{sign} +\DeclareMathOperator{\Tr}{Tr} +\let\ab\allowbreak diff --git a/latex_templates/ICLR2022/methodology.tex b/latex_templates/ICLR2022/methodology.tex new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/latex_templates/ICLR2022/natbib.sty b/latex_templates/ICLR2022/natbib.sty new file mode 100644 index 0000000000000000000000000000000000000000..ff0d0b91b6ef41468c593a0ca40a81f9a183b055 --- /dev/null +++ b/latex_templates/ICLR2022/natbib.sty @@ -0,0 +1,1246 @@ +%% +%% This is file `natbib.sty', +%% generated with the docstrip utility. +%% +%% The original source files were: +%% +%% natbib.dtx (with options: `package,all') +%% ============================================= +%% IMPORTANT NOTICE: +%% +%% This program can be redistributed and/or modified under the terms +%% of the LaTeX Project Public License Distributed from CTAN +%% archives in directory macros/latex/base/lppl.txt; either +%% version 1 of the License, or any later version. +%% +%% This is a generated file. +%% It may not be distributed without the original source file natbib.dtx. +%% +%% Full documentation can be obtained by LaTeXing that original file. +%% Only a few abbreviated comments remain here to describe the usage. +%% ============================================= +%% Copyright 1993-2009 Patrick W Daly +%% Max-Planck-Institut f\"ur Sonnensystemforschung +%% Max-Planck-Str. 2 +%% D-37191 Katlenburg-Lindau +%% Germany +%% E-mail: daly@mps.mpg.de +\NeedsTeXFormat{LaTeX2e}[1995/06/01] +\ProvidesPackage{natbib} + [2009/07/16 8.31 (PWD, AO)] + + % This package reimplements the LaTeX \cite command to be used for various + % citation styles, both author-year and numerical. It accepts BibTeX + % output intended for many other packages, and therefore acts as a + % general, all-purpose citation-style interface. + % + % With standard numerical .bst files, only numerical citations are + % possible. With an author-year .bst file, both numerical and + % author-year citations are possible. + % + % If author-year citations are selected, \bibitem must have one of the + % following forms: + % \bibitem[Jones et al.(1990)]{key}... + % \bibitem[Jones et al.(1990)Jones, Baker, and Williams]{key}... + % \bibitem[Jones et al., 1990]{key}... + % \bibitem[\protect\citeauthoryear{Jones, Baker, and Williams}{Jones + % et al.}{1990}]{key}... + % \bibitem[\protect\citeauthoryear{Jones et al.}{1990}]{key}... + % \bibitem[\protect\astroncite{Jones et al.}{1990}]{key}... + % \bibitem[\protect\citename{Jones et al., }1990]{key}... + % \harvarditem[Jones et al.]{Jones, Baker, and Williams}{1990}{key}... + % + % This is either to be made up manually, or to be generated by an + % appropriate .bst file with BibTeX. + % Author-year mode || Numerical mode + % Then, \citet{key} ==>> Jones et al. (1990) || Jones et al. [21] + % \citep{key} ==>> (Jones et al., 1990) || [21] + % Multiple citations as normal: + % \citep{key1,key2} ==>> (Jones et al., 1990; Smith, 1989) || [21,24] + % or (Jones et al., 1990, 1991) || [21,24] + % or (Jones et al., 1990a,b) || [21,24] + % \cite{key} is the equivalent of \citet{key} in author-year mode + % and of \citep{key} in numerical mode + % Full author lists may be forced with \citet* or \citep*, e.g. + % \citep*{key} ==>> (Jones, Baker, and Williams, 1990) + % Optional notes as: + % \citep[chap. 2]{key} ==>> (Jones et al., 1990, chap. 2) + % \citep[e.g.,][]{key} ==>> (e.g., Jones et al., 1990) + % \citep[see][pg. 34]{key}==>> (see Jones et al., 1990, pg. 34) + % (Note: in standard LaTeX, only one note is allowed, after the ref. + % Here, one note is like the standard, two make pre- and post-notes.) + % \citealt{key} ==>> Jones et al. 1990 + % \citealt*{key} ==>> Jones, Baker, and Williams 1990 + % \citealp{key} ==>> Jones et al., 1990 + % \citealp*{key} ==>> Jones, Baker, and Williams, 1990 + % Additional citation possibilities (both author-year and numerical modes) + % \citeauthor{key} ==>> Jones et al. + % \citeauthor*{key} ==>> Jones, Baker, and Williams + % \citeyear{key} ==>> 1990 + % \citeyearpar{key} ==>> (1990) + % \citetext{priv. comm.} ==>> (priv. comm.) + % \citenum{key} ==>> 11 [non-superscripted] + % Note: full author lists depends on whether the bib style supports them; + % if not, the abbreviated list is printed even when full requested. + % + % For names like della Robbia at the start of a sentence, use + % \Citet{dRob98} ==>> Della Robbia (1998) + % \Citep{dRob98} ==>> (Della Robbia, 1998) + % \Citeauthor{dRob98} ==>> Della Robbia + % + % + % Citation aliasing is achieved with + % \defcitealias{key}{text} + % \citetalias{key} ==>> text + % \citepalias{key} ==>> (text) + % + % Defining the citation mode and punctual (citation style) + % \setcitestyle{} + % Example: \setcitestyle{square,semicolon} + % Alternatively: + % Use \bibpunct with 6 mandatory arguments: + % 1. opening bracket for citation + % 2. closing bracket + % 3. citation separator (for multiple citations in one \cite) + % 4. the letter n for numerical styles, s for superscripts + % else anything for author-year + % 5. punctuation between authors and date + % 6. punctuation between years (or numbers) when common authors missing + % One optional argument is the character coming before post-notes. It + % appears in square braces before all other arguments. May be left off. + % Example (and default) \bibpunct[, ]{(}{)}{;}{a}{,}{,} + % + % To make this automatic for a given bib style, named newbib, say, make + % a local configuration file, natbib.cfg, with the definition + % \newcommand{\bibstyle@newbib}{\bibpunct...} + % Then the \bibliographystyle{newbib} will cause \bibstyle@newbib to + % be called on THE NEXT LATEX RUN (via the aux file). + % + % Such preprogrammed definitions may be invoked anywhere in the text + % by calling \citestyle{newbib}. This is only useful if the style specified + % differs from that in \bibliographystyle. + % + % With \citeindextrue and \citeindexfalse, one can control whether the + % \cite commands make an automatic entry of the citation in the .idx + % indexing file. For this, \makeindex must also be given in the preamble. + % + % Package Options: (for selecting punctuation) + % round - round parentheses are used (default) + % square - square brackets are used [option] + % curly - curly braces are used {option} + % angle - angle brackets are used