Source: http://www.nsfcvdi.org/wordpress/research-impacts-2/research-impacts/publications/
Timestamp: 2019-04-24 00:11:10+00:00

Document:
Adams, Stephen; Beling, Peter A; Greenspan, Steve; Velez-Rojas, Maria; Mankovski, Serge. (2018). Model-Based Trust Assessment for Internet of Things Networks. 2018 17th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/12th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE). 1838-1843.
Wang, Yang; Adams, Stephen; Beling, Peter; Greenspan, Steven; Rajagopalan, Sridhar; Velez-Rojas, Maria; Mankovski, Serge; Boker, Steven; Brown, Donald. (2018). Privacy preserving distributed deep learning and its application in credit card fraud detection. 2018 17th IEEE International Conference on Trust, Security and Privacy In Computing And Communications/12th IEEE International Conference on Big Data Science and Engineering (TrustCom/BigDataSE).
D. Zarella, M.R. Quaschnick, D.E. Breen and F.U. Garcia. Estimation of Fine-Scale Histologic Features at Low Magnification. Archives of Pathology & Laboratory Medicine. Vol. 142, No. 11. November 2018. p. 1394-1402.
Xiao-Fei Zhang, Le Ou-Yang, Shuo Yang, Xiaohua Hu, Hong Yan. DiffGraph: an R package for identifying gene network rewiring using differential graphical models. Bioinformatics 34(9): 1571-1573 (2018).
Jianliang Gao, Bo Song, Xiaohua Hu, Fengxia Yan, Jianxin Wang. ConnectedAlign: a PPI network alignment method for identifying conserved protein complexes across multiple species. BMC Bioinformatics 19(9): 129-135 (2018).
Yuanyuan Ma, Xiaohua Hu, Tingting He, Xianchao Zhu, Meijun Zhou, Xingpeng Jiang. ESNMF: Evolutionary Symmetric Nonnegative Matrix Factorization for Dissecting Dynamic Microbial Networks. ICIC (3) 2018: 7-18.
Linh Le, Ying Xie, and V. V. Raghavan Deep Similarity-Enhanced K Nearest Neighbors. Special session on Information Granulation in Data Science and Scalable Computing. 2018 IEEE Data. Seattle, WA. December 2018.
Siva R. Venna, Amirhossein Tavanaei, Raju N. Gottumukkala, Vijay V. Raghavan, Anthony S. Maida, Stephen Nichols. A Novel Data-Driven Model for Real-Time Influenza Forecasting. IEEE Access. Volume 7. Issue 1. Pages 7691-7701. December 19, 2018.
Satya Katragadda, Jian Chen, and S. Abbady. Spatial hotspot detection using polygon propagation. International Journal of Digital Earth. 2018.
Satya Katragadda, Raju Gottumukkala, Murali Pusala, Vijay Raghavan and Jessica Wojtkiewicz. Distributed Real Time Link Prediction on Graph Streams. 2018 IEEE International Conference on Big Data (Big Data). Seattle, WA, USA. December 2018. pp. 2912-2917.
Adrian Mead, Tyler Lewris, Sai Prasanth, Stephen Adams, Peter Alonzi, Peter Beling. Detecting Fraud in Adversarial Environments: A Reinforcement Learning Approach. Systems and Information Engineering Design Symposium 2018.
Abhimanyu Roy, Jingyi Sun, Robert Mahoney, Loreto Alonzi, Stephen Adams, Peter Beling. Deep Learning Detecting Fraud in Credit Card Transactions. Systems and Information Engineering Design Symposium 2018.
Tyler Cody, Stephen Adams, Peter A. Beling. A Utilitarian Approach to Adversarial Learning in Credit Card Fraud Detection. Systems and Information Engineering Design Symposium 2018.
Im, Taeyu. “Smartphone based approximate localization using user highlighted texts from images,” Pervasive and mobile computing, v. 46, 2018.
Park, Ji Hwan. “Transfer Function-Guided Saliency-Aware Compression for Transmitting Volumetric Data,” IEEE transactions on multimedia, 2018.
D. Lytras, V. V. Raghavan and E. Damiani (Guest Editors). Special Issue on Big Data and Data Analytics Research: Challenging Data and Web Science for Next Generation High Performance Information Systems. International Journal on Semantic Web and Information Systems. Volume 13, No.1. January – March 2017. IGI Global, Hershey, PA.
D. Lytras, V. V. Raghavan and E. Damiani. Big Data and Data Analytics Research: From Metaphors to Value Space for Collective Wisdom in Human Decision Making and Smart Machines. International Journal on Semantic Web and Information Systems. Volume 13, No. 1. pp. 1 – 10. January – March, 2017.
Mary Frances Zeager, Aksheetha Sridhar, Nathan Fogal, Stephen Adams, Donald E. Brown, and Peter A. Beling. Adversarial Learning in Credit Card Fraud Detection. Systems and Information Engineering Design Symposium 2017.
Gabriel Rushin, Cody Stancil, Muyang Sun, Stephen Adams, Peter Beling. Horse Race Analysis in Credit Card Fraud—Deep Learning, Logistic Regression, and Gradient Boosted Tree. Systems and Information Engineering Design Symposium 2017.
Adams, Stephen and Meekins, Ryan and Beling, Peter A. (2017). An Empirical Evaluation of Techniques for Feature Selection with Cost. 2017 IEEE International Conference on Data Mining Workshops (ICDMW). 834 to 841.
Lee, K. and Rucker, M. and Scherer, W. and Beling, P. and Gerber, M. and Kang, H. (2017). Agent-based model construction using inverse reinforcement learning. 2017 Winter Simulation Conference (WSC). 1264-1275.
Zhengqiao Zhao, Jason Rollins, Linge Bai. Incremental Author Name Disambiguation for Scientific Citation Data. 2017 IEEE International Conference on Data Science and Advanced Analytics (DSAA), 19-21 Oct. 2017.
Zheng Chen, Xinli Yu, Bo Song, Jianliang Gao, Wei-Shih Yang. Community-Based Network Alignment for Large Attribute Network. 26th ACM International Conference on Information and Knowledge Management (CIKM 2017), Singapore, Nov 6-10, 2017: 587-596.
Yuan Ling, Yuan An, Mengwen Liu, Sadid A. Hasan, Ye-tian Fan. Integrating extra knowledge into word embedding models for biomedical NLP tasks. 2017 International Joint Conference on Neural Networks (IJCNN 2017), Anchorage, AK, May 14-19 2017: 968-975.
Zheng Chen, Xinli Yu, Chi Zhang, Jin Zhang, Cui Lin, Erjia Yan, and Wei-Shih Yang. Fast Botnet Detection From Streaming Logs Using Online Lanczos Method. IEEE 2017 International Conference on Big Data (IEEE BigData 2017), Boston, MA, Dec 11-16, 2017.
Katragadda, R. G. Benton and V. V. Raghavan. Sub-Event Detection from Tweets. Special Session on Datastream Mining (IJCNN-S12+29), 2017 Int’l Joint Conference on Neural Networks (IJCNN 2017), Anchorage, AK, May 2017.
A. Sharif and V. V. Raghavan. Link Prediction Based Hybrid Recommendation System using User-Page Preference Graphs. 2017 Int’l Joint Conference on Neural Networks (IJCNN 2017), Anchorage, AK, May 2017.
B. Duggimpudi, S. Abbady, J. Chen, V.V. Raghavan. Spatio-Temporal Outlier Detection Algorithms Based on Computing Behavioral Outlierness Factor. Data & Knowledge Engineering. An Elsevier Journal, 2017.
Abbady, C. Ke, J. Lavergne, J. Chen. V.V. Raghavan, R. Benton. Online Mining for Association Rules and Collective Anomalies in Data Streams. Second Workshop on Real-time and Stream Processing in Big Data, in 2017 IEEE International Conference on Big Data. Boston, MA, 2017, pp. 1 – 10.
M. Borrok, J. Chen. H. Eldardiry, E. Habib. A Framework for Incorporating the Impact of Water Quality on Water Supply Stress: An Example from Louisiana, USA. Journal of the American Water Resources Association (JAWAR) 2017.
K. Pusala, R. G. Benton, V. V. Raghavan and R. N. Gottumukkala. Supervised approach to rank predicted links using interestingness measures. 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Kansas City, MO, 2017, pp. 1085-1092.
Singh, W. Xu and V. V. Raghavan. Descriptor based protein structure representation using triangular spatial relationships in 3-D. 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Kansas City, MO, USA, 2017, pp. 1114-1118.
Vijay Raghavan, Srinivas Aluru, George Karypis, Lucio Miele and Xindong Wu (Editors). Proceedings of the 2017 IEEE International Conference on Data Mining, 18-21 November 2017, New Orleans, LA, USA, IEEE Computer Society, Los Alamitos, CA.
Raju Gottumukkala, Xia Ning, Guozhu Dong, Vijay Raghavan, Srinivas Aluru, George Karypis, Lucio Miele and Xindong Wu (Editors). Proceedings of the 2017 IEEE International Conference on Data Mining (Workshops), 18-21 November 2017, New Orleans, LA, USA, IEEE Computer Society, Los Alamitos, CA.
Steven S. Skiena. The Data Science Design Manual (Texts in Computer Science). Springer. 2017. ISBN-13: 978-3319554433.
Satya Katragadda, Ryan Benton, and Vijay Raghavan, Framework for Real-Time Event Detection using Multiple Social Media Sources Hawaii International Conference on System Sciences, Hilton Waikoloa Village, Hawaii, 8 pages, January 4 – 8, 2017.
D. Zarella, F.U. Garcia and D.E. Breen. A Template Matching Model for Nuclear Segmentation in Digital Images of H&E Stained Slides. Proc. 9th International Conference on Bioinformatics and Biomedical Technology, May 2017, pp. 11-15.
D. Zarella, C. Yeoh, D.E. Breen and F.U. Garcia. An Alternative Reference Space for H&E Color Normalization. PLoS ONE, Vol. 12, No. 3, March 2017, p. e0174489.
Mengwen Liu, Wanying Ding, Dae Hoon Park, Yi Fang, Rui Yan, Xiaohua Hu. Which used product is more sellable? A time-aware approach. Inf. Retr. Journal20(2): 81-108 (2017).
JianLiang Gao, Bo Song, Wanyign Ding, Weimao Ke, Xiaohua Hu. Counter Deanonymization Query: H-index Based K-Anonymization Privacy Protection for Social Networks. SIGIR 2017; pp809-812.
Zheng Chen, Xinli Yu, Jianliang Gao, Bo Song, Xiaohua Hu, Wei-Shih Yang. Community-based Network Alignment for Large Attributed Network. CIKM 2017.
Guanqun Cao, Alexandros Iosifidis and Moncef Gabbouj. Multi-view Nonparametric Discriminant Analysis for Image Retrieval and Recognition. Signal Processing Letters, vol. 24, no. 10, pp. 1537 – 1541, 2017.
Serkan Kiranyaz, Turker Ince, Alexandros Iosifidis and Moncef Gabbouj. Progressive Operational Perceptrons. Neurocomputing, Volume 224, 8 February 2017, Pages 142–154. (http://dx.doi.org/10.1016/j.neucom.2016.10.044).
Aytekin, A. Iosifidis, S. Kiranyaz and M. Gabbouj. Learning Graph Affinities for Spectral-based Salient Object Detection. Pattern Recognition, Volume 64, April 2017, Pages 159–167.
Caglar Aytekin, Serkan Kiranyaz and Moncef Gabbouj. Extended Quantum Cuts for Unsupervised Salient Object Extraction. Multimedia Tools and Applications, vol. 76, no. 8, April 2017, pp 10443–10463, DOI: 10.1007/s11042-016-3431-1.
Serkan Kiranyaz, Turker Ince and Moncef Gabbouj. Personalized Monitoring and Advance Warning System for Cardiac Arrhythmias (rdcu.be/vfYE). Nature Scientific Reports, 24 August 2017, DOI 10.1038/s41598-017-09544-z (SREP-16-52549-T).
Joel Pyykkö, Dorota Głowacka. Dynamic Exploratory Search in Content-Based Image Retrieval. Proceedings of the Scandinavian Conference on Image Analysis (SCIA’2017).
Alan Medlar, Joel Pyykkö, Dorota Głowacka. Towards Fine-Grained Adaptation of Exploration/Exploitation in Information Retrieval. IUI ’17 Proceedings of the 22nd International Conference on Intelligent User Interfaces.
S. Cinar, B. Genc, H. Sever and V. V. Raghavan, “Analyzing Structure of Terrorists Networks by Using Graph Metrics,” The 8th IEEE International Conference on Big Knowledge (IEEE ICBK 2017), Hefei, PRC, pp. 9 – 16, Aug. 2017.
Nasser, H. Sever and V. V. Raghavan, “Utilization Rough Sets for Intrusion Detection,” Position Paper, Joint 17th World Congress of International Fuzzy Systems Association and 9th International Conference on Soft Computing and Intelligent Systems (IFSA-SCIS 2017), Otsu, Japan, June 2017.
Nadeem, Saad. “LMap: Shape-Preserving Local Mappings for Biomedical Visualization,” IEEE transactions on visualization and computer graphics, v. 11, 2017.
Dmitriev, Konstantin. “Classification of Pancreatic Cysts in Computed Tomography Images Using a Random Forest and Convolutional Neural Network Ensemble,” Medical Image Computing and Computer-Assisted Intervention? MICCAI 2017, v. 09/04/2, 2017.
Ming Chen, Geetika Bangera, Dean Hildebrand Farhaan Jalia, Geoff Kuenning, Henry Nelson, and Erez Zadok. vNFS: Maximizing NFS performance with compounds and vectorized I/O. ACM Transactions on Storage (TOS), 13(7), September 2017.
Erez Zadok, Dean Hildebrand, Geoff Kuenning, and Keith Smith. POSIX is dead! Long live… errr… what exactly? In HotStorage ’17: Proceedings of the 9th USENIX Workshop on Hot Topics in Storage, Santa Clara, CA, July 2017. USENIX. WACI track.
Ming Chen, Dean Hildebrand, Henry Nelson, Jasmit Saluja, Ashok Subramony, and Erez Zadok. vNFS: Maximizing NFS performance with compounds and vectorized I/O. In Proceedings of the 15th USENIX Conference on File and Storage Technologies (FAST), pages 301–314, Santa Clara, CA, February/March 2017. USENIX Association. (Nominated for best paper award).
Bharath Kumar Reddy Vangoor, Vasily Tarasov, and Erez Zadok. To FUSE or not to FUSE: Performance of user-space file systems. In Proceedings of the 15th USENIX Conference on File and Storage Technologies (FAST), pages 59–72, Santa Clara, CA, February/March 2017. USENIX Association.
Zhen Cao, Vasily Tarasov, Hari Raman, Dean Hildebrand, and Erez Zadok. On the performance variation in modern storage stacks. In Proceedings of the 15th USENIX Conference on File and Storage Technologies (FAST), pages 329–343, Santa Clara, CA, February/March 2017. USENIX Association.
Chen, Y., Perozzi, B., & Skiena, S. Vector-based similarity measurements for historical figures. Information Systems, 64, 163-174. 2017.
Ye, J., Han, S., Hu, Y., Coskun, B., Liu, M., Qin, H., & Skiena, S. Nationality Classification Using Name Embeddings. In Proceedings of the 2017 ACM on Conference on Information and Knowledge Management (pp. 1897-1906). ACM. November 2017.
Skiena, S. S., & Ward, C. B. (2017). Who’s bigger? Where computer scientists really rank. BSHM Bulletin: Journal of the British Society for the History of Mathematics, 32(3), 257-264.
Chen, H., Anantharam, A. R., & Skiena, S. DeepBrowse: Similarity-Based Browsing Through Large Lists. In International Conference on Similarity Search and Applications (pp. 300-314). Springer, Cham. October 2017.
Nguyen, V., Vicente, T., Zhao, M., Hoai, M. & Samaras, D. Shadow Detection with Conditional Generative Adversarial Networks. Proceedings of International Conference on Computer Vision (ICCV). 2017.
Liu, Y., Hoai, M., Shao, M. & Kim, T-K. Latent Bi-constraint SVM for Video-based Object Recognition. IEEE Transactions on Circuits and Systems for Video Technology. 2017.
Ma, K., Hoai, M., & Samaras, D. Large-scale Continual Road Inspection: Visual Infrastructure Assessment in the Wild. Proceedings of British Machine Vision Conference (BMVC). 2017.
Wang, B., Yager, K., Yu, D., & Hoai, M. X-ray Scattering Image Classification Using Deep Learning. Proceedings of Winter Conference on Applications of Computer Vision (WACV). 2017.
Kelton, C., Ryoo, J., Balasubramanian, A., & Das, S. R. Improving User Perceived Page Load Times Using Gaze. In NSDI (pp. 545-559). March 2017.
Chakraborty, A., Rahman, M. S., Gupta, H., & Das, S. R. Specsense: Crowdsensing for efficient querying of spectrum occupancy. In INFOCOM 2017-IEEE Conference on Computer Communications, IEEE (pp. 1-9). IEEE. May 2017.
Dasari, M., Kelton, C., Nejati, J., Balasubramanian, A., & Das, S. R. Demystifying Hardware Bottlenecks in Mobile Web Quality of Experience. In Proceedings of the SIGCOMM Posters and Demos (pp. 43-45). ACM. August 2017.
Yusuf Osmanlıoglu, Ali Shokoufandeh, Multilayer Matching of Metric Structures Using Hierarchically Well-separated Trees Pattern Recognition Letters Journal. 2016.
Ezgi Can Ozan, Serkan Kiranyaz, Moncef Gabbouj, and X. Hu, Self-Organizing Binary Encoding for Approximate Nearest Neighbor Search Proc. 24th European Signal Processing Conference (EUSIPCO 2016).
Caglar Aytekin, Serkan Kiranyaz, Alexandros Iosifidis and Moncef Gabbouj, Recent Advances in Salient Object Detection – Towards Object Recognition in Bid Media Data Futura — Big Data, vol. 35, no. 2, pp. 80-92, 2016.
Morteza Zabihi, Ali B. Rad, Serkan Kiranyaz, Moncef Gabbouj and Aggelos K. Katsaggelos, PhysioNet/CinC Challenge: Normal/Abnormal PCG Classification using an Ensemble of Support Vector Machines Proceedings of Computing in Cardiology, CinC 2016, Vancouver, Canada, September 11 – 14, 2016.
Jenni Raitoharju, Serkan Kiranyaz, Moncef Gabbouj, Feature synthesis for image classification and retrieval via one-against-all perceptrons Neural Computing and Applications, 29 July 2016, p. 1-15.
Jenni Raitoharju, Serkan Kiranyaz and Moncef Gabbouj, Training Radial Basis Function Neural Networks for Classiﬁcation via Class-speciﬁc Clustering IEEE Transactions on Neural Networks and Learning Systems, vol, 27, Dec. 2016.
Alexandros Iosifidis and Moncef Gabbouj Supervised learning based on deep randomized networks Proc. IEEE International Conference on Acoustic Speech and Signal Processing, ICASSP 2016, 21-25 March 2016, Shanghai, China, pp. 2584-2588.
A. Iosifidis and M. Gabbouj Combining Multi-class Maximum Margin Classification with Linear Discriminant Analysis for Human Action Recognition Proc. IEEE International Conference on Image Processing (ICIP), Arizona, USA, 2016.
Alexandros Iosifidis and Moncef Gabbouj, Multi-class Support Vector Machine Classifiers using Intrinsic and Penalty Graphs Pattern Recognition, vol. 55, July 2016, pp. 231-246.
S. Kiranyaz, M.-A. Waris, I. Ahmad, R. Hamila, and M. Gabbouj, Face Segmentation ın thumbnail Images by Data-Adaptive Convolutional Segmentation Networks Proc. Int. Conf. on Image Processing, (ICIP), Phoenix, Arizona, USA, September 25-28, 2016.
Osama Abdeljaber, Onur Avci, Serkan Kiranyaz, Moncef Gabbouj, Daniel J. Inman, Real-Time Vibration-Based Structural Damage Detection Using One-Dimensional Convolutional Neural Networks Journal of Sound and Vibration, in press 2016.
Jian Chen, Shaaban Abbady, Maria Bala Duggimpudi, Spatio-Temporal Outlier Detection: Did Buoys Tell Where the Hurricanes Were? Papers in Applied Geography, May 2016.
Satya Katragadda, Ryan Benton, Shahid Virani, and Vijay Raghavan, Detection of Event Onset using Twitter IEEE International Joint Conference on Neural Networks, Vancouver, Canada, pp.1539-1546, July 25-29, 2016.
Y. Xie, Jing He, and V. Raghavan, Identifying Minimum-Sized Influential Vertices on Large-Scale Weighted Graphs: A Big Data Perspective Data Science and Big Data Computing: Frameworks and Methodologies. Springer-Verlag, Berlin-Heidelberg, pp. 79-92, 2016 (ISBN 978-3-319-31861-5).
M. K. Pusala, M. A. Salehi, J. R. Katukuri, Y. Xie, and V. V. Raghavan, Massive Data Analysis: Tasks, Tools, Applications and Challenges Big Data Analytics- Methods and Applictions. Chapter 2, Springer-Verlag, New Delhi, pp. 33-46, 2016 (ISBN 978-8-132-23626-9).
S. R. Venna, R. N. Gottumukkala and V. V. Raghavan, Visual Analytic Decision-Making Environments for Large-scale Time-evolving Graphs Cognitive Computing- Theory and Applications: Handbook of Statistics (Volume 35). Elsevier, Amsterdam, pp. 81 – 116, 2016.
V. N. Gudivada, V. V. Raghavan, V. Govindaraju , C. R. Rao (Editors), Cognitive Computing- Theory and Applications: Handbook of Statistics Cognitive Computing- Theory and Applications: Handbook of Statistics (Volume 35), September 2016, ISBN: 978-0-444-63744-4, Elsevier, Amsterdam, Netherlands.
V.N. Gudivada, Dhana Rao and V. V. Raghavan, Renaissance in Database Management: Navigating the Landscape of Candidate Systems IEEE Computer, Vol. 49, No. 4, pp. 31 – 42, April. 2016.
M. B. Duggimpudi, A. Moursy, E. Ali and V. V. Raghavan, An Ontology-based Architecture for Providing Insights in Wireless Networks Domain Proc. of the IEEE/WIC/ACM International Conference on Web Intelligence (WI 2016), Omaha, NE, Oct. 2016.
Honglei Zhang, Jenni Raitoharju, Serkan Kiranyaz and Moncef Gabbouj. Limited random walk algorithm for big graph data clustering. Journal of Big Data, DOI: 10.1186/s40537-016-0060-5. 1 December 2016.
Alexandros Iosifidis and Moncef Gabbouj. Scaling up Class-Specific Kernel Discriminant Analysis for large-scale Face Verification. IEEE Transactions on Information Forensics & Security, vol. 11, no. 11, pp. 2453 – 2465, 2016.
Alexandros Iosifidis and Moncef Gabbouj. Nyström-based approximate kernel subspace learning. Pattern Recognition, vol. 57, no. C, September 2016, pp. 190-197.
Ezgi Can Ozan, Serkan Kiranyaz, Moncef Gabbouj. Competitive Quantization for Approximate Nearest Neighbor Search. IEEE Transactions on Knowledge and Data Engineering, vol. 28, no. 11, 2016, pp. pp. 2884 – 2894.
Serkan Kiranyaz, Turker Ince, Levent Eren, M. Askar and Moncef Gabbouj. Real-Time Motor Fault Detection by 1D Convolutional Neural Networks, IEEE Transaction on Industrial Electronics, vol. 63, no. 11, 2016, pp. 7067 – 7075, DOI: 10.1109/TIE.2016.2582729.
Ezgi Ozan Can, Serkan Kiranyaz and Moncef Gabbouj. K-Subspaces Quantization for Approximate Nearest Neighbor Search, IEEE Transactions on Knowledge and Data Engineering, vol. 28, no. 7, 1 July 2016, pp. 1722 – 1733.
Joel Pyykkö, Dorota Głowacka. Interactive Content-Based Image Retrieval with Deep Neural Networks. Symbiotic 2016: Symbiotic Interaction.
Pedram Daee, Joel Pyykkö, Dorota Głowacka, Samuel Kaski. Interactive Intent Modeling from Multiple Feedback Domains. IUI ’16 Proceedings of the 21st International Conference on Intelligent User Interfaces.
Rui Yan, Ian E.H. Yen, Cheng-Te Li, Shiqi Zhao, Xiaohua Hu, Tackling the Achilles Heel of Social Networks: Influence Propagation based Language Model Smoothing WWW 2015. Florence 18-22, May 2015.
Mengwen Liu, Yuan An, et al., Constraint Multi-Instance Multi-Label Model for Distant Supervision of Biomedical Relation Extraction IEEE IEEE/ACM Transactions on Computational Biology and Bioinformatics. 2015.
Meen Chul Kim, Chaomei Chen, A scientometric review of emerging trends and new developments in recommendation systems. Scientometrics, 104(1), 239-263. 2015.
Anton Slutsky, Xiaohua Hu, Yuan An, Learning Focused Hierarchical Topic Models with Semi-Supervision in Microblogs PAKDD 2015.
Wanying Ding, Yue Shang, Lifan Guo, Xiaohua Hu, Rui Yan, Tingting He, Video Popularity Prediction by Sentiment Propagation via Implicit Network regular paper, CIKM 2015.
Rui Yan, Xiang Li, Mengwen Liu, Xiaohua Hu, Tackling Sparsity, the Achilles Heel of Social Networks: Language Model Smoothing via Social Regularization ACL (2) 2015: 623-629.
Yue Shang, Wanying Ding, Haohong Wang, Lifan Guo, Mengwen Liu, Xiaoli Song, Xiaohua Hu, Yuan, An Scalable User Intent Mining using a Multimodal Restricted Boltzmann Machine. International Conference on Computing Networking and Communications(ICNC 2015). Anaheim, California, USA. 2015.
Yusuf Osmanlioglu, Sven J. Dickinson, and Ali Shokoufandeh, Unsupervised Motion Segmentation Using Metric Embedding of Features Similarity-Based Pattern Recognition – Third International Workshop, (SIMBAD}. 2015. Copenhagen, Denmark. October 12-14, 2015. PP 133-145.
G. Rama Murthy, Moncef Gabbouj and Iftikhar Ahmad, Image Retrieval: Information and Rough Set Theories Proc. International Conference on Image and Signal Processing, August 2015, Elsevier Publishers.
Ezgi Can Ozan, Serkan Kiranyaz, Moncef Gabbouj, and X. Hu, Joint K-Means Quantization for Approximate Nearest Neighbor Search Proc. 2016 23rd International Conference on Pattern Recognition (ICPR 2016).
G. Rama Murthy and Moncef Gabbouj, Linear Congruential Sequences: Feedback and Recurrent Neural Networks Proc. Third International Conference on Emerging Research in Computing, Information and Communication and Applications (ERCICA 2015).
G. Rama Murthy, Berkay Kicanoglu and Moncef Gabbouj, On the Dynamics of a Recurrent Hopfield Network Proceedings of IEEE International Joint Conference on Neural Networks (IJCNN 2015), July 2015, Pages: 1 – 8, DOI: 10.1109/IJCNN.2015.7280504.
G. Rama Murthy and Moncef Gabbouj, On the Design of Hopfield Neural Networks: Synthesis of Hopfield Type Associative Memories Proceedings of IEEE International Joint Conference on Neural Networks (IJCNN 2015), July 2015, Pages: 1 – 8, DOI: 10.1109/IJCNN.2015.7280299.
G. Rama Murthy and Moncef Gabbouj, Existence and Synthesis of Complex Hopfield Type Associative Memories Proceedings of International Conference on Artificial Neural Networks, June 2015, Lecture Notes in Computer Science, Springer, vol 9095, pp 356-369.
Caglar Aytekin, Ezgi Can Ozan, Serkan Kiranyaz, Moncef Gabbouj, Visual Saliency by Extended Quantum Cuts Proceedings of the IEEE International Conference on Image Processing, ICIP 2015, Quebec City, 27-30 September 2015.
Ying Xie, Tom Johnsten, Vijay V. Raghavan, Ryan G. Benton, and William Bush, A Comprehensive Granular Model for Decision Making with Complex Data Granular Computing and Decision-Making: Interactive and Iterative Approaches, Witold Pedrycz and Shyi-Ming Chen (ed.), Springer, pp. 36-46. 2015.
Sonya Hsu, Ryan Benton, and Raju Gottumukkala, Real-Time Flu Monitoring System and Decision Informatics In Hawaii International Conference on System Sciences, Kauai, Hawaii, pp. 2794-2803, January 5-8, 2015.
Venkat N. Gudivada, Ricardo Baeza-Yates, Vijay Raghavan Big Data: Promises and Problems IEEE Computer 48(3): 20 – 23. February 2015.
Nicholas G. Lipari and Christoph W. Borst, Handymenu: Integrating Menu Selection into a Multifunction Smartphone-based VR Controller Proceedings of IEEE 3D User Interfaces (3DUI) 2015, pp. 129-132.
Raju N. Gottumukkala, Siva R. Venna, Vijay Raghavan, Visual Analytics of Time Evolving Large-scale Graphs The IEEE Intelligent Informatics Bulletin. December 2015.
N. M. Hk. AlSudairy, A. M. Hafez, V. V. Raghavan and H. I. Mathkour, Candidate Graph Generation Algorithm Proc. of the 9th International Conf. on Computer Engineering and Applications (CEA 2015)- in conjunction with WSEAS, Feb. 2015.
Vijay Raghavan, Satya Katragadda, Harika Karnati, Murali Pusala, and Ryan Benton, Detecting Adverse Drug Effects Using Link Classification on Twitter Data IEEE International Conference on Bioinformatics and Biomedicine. Bethesda, Maryland. pp. 675-679. Nov 9 – 12, 2015.
Elshaimaa Ali and Vijay Raghavan, Extending SKOS: A Wikipedia-based Unified Annotation Model for Creating Interoperable Domain Ontologies 22nd International Symposium on Methodologies for Intelligent Systems (ISMIS 2015). Springer LNCS. Lyon, France. October 2015.
V.N. Gudivada, Dhana Rao, Vijay Raghavan, Big Data Driven Natural Language Processing and Applications Big Data Analytics- Handbook of Statistics. Volume 33, Elsevier, pp. 203-238, July 2015.
V. Govindaraju, Vijay Raghavan, C. R. Rao (Eds.), Big Data Analytics- Handbook of Statistics Volume 33, Elsevier, July 2015.
Yuan Ling, Yuan An, Xiaohua Hu A, Matching Framework for Modeling Symptom and Medication Relationships from Clinical Notes In the IEEE Conference on Bioinformatics and Biomedicine (BIBM14), pages 515-520.
Yizhou Zang, Yuan An, and Xiaohua Hu, Automatically Recommending Healthy Living Programs to Patients with Chronic Diseases through Hybrid Content-Based and Collaborative Filtering In IEEE International Conference on Bioinformatics and Biomedicine (BIBM) 2014, Belfast, UK, pages 578-582.
Mengwen Liu, Yuan Ling, Yuan An, Xiaohua Hu, Alan Yagoda, and Rick Misra, Relation Extraction from Biomedical Literature with Minimal Supervision and Grouping Strategy In the IEEE Conference on Bioinformatics and Biomedicine (BIBM14), pages 444-449.
Elshaimaa Ali, Michael Lauruhn, Vijay Raghavan, Wikipedia-based Extraction of Lightweight Ontologies for Concept Level Annotation International Conference on Dublin Core and Metadata Applications (DC 2014). Austin, Tx. October 2014.
Mohammad Amir Sharif, Vijay V. Raghavan, A Clustering Based Scalable Hybrid Approach for Web Page Recommendation Proc. of the 2014 IEEE International Conference on Big Data: 2nd Workshop on Scalable Machine Learning: Theory and Applications, Oct. 2014, Washington, D.C.
Satya Katragadda, Miao Jin, Vijay V. Raghavan, An Unsupervised Approach to Identify Location Based on the Content of User’s Tweet History AMT 2014: 311-323.
Mohammad Amir Sharif, Vijay V. Raghavan, A Large-Scale, Hybrid Approach for Recommending Pages Based on Previous User Click Pattern and Content ISMIS 2014: 103-112.
R. Khare, Y. An, S. Wolf, P. Nyirjesy, L. Liu, and E. Chou, Understanding the EMR Error Control Practices among Gynecologic Physicians In iConference 2013, 13 pages Fort Worth, Texas, 2013.
Yue Shang, Yuan An, Xiaohua Hu, Mi Zhang, and Xia Lin, Enhancing Entity Annotation using Web Service and Ontology Hierarchy in Biomedical Domains In IEEE BIBM 2013. pages 465-468. Shanghai, China. Dec. 18-21, 2013.
V. V. Raghavan and Elshaimaa Ali, Modeling the Wikipedia for Web Annotation: Towards Building a Semantic Annotation Framework In proceeding of: IADIS International Conference WWW/INTERNET 2013, Fort Worth, TX, pp. 243 – 250, Oct. 2013.
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