cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25440/smu.12062733
title: Online Feature Selection and Its Applications

description: Feature selection is an important technique for data mining before a machine learning algorithm is applied. Despite its importance, most studies of feature selection are restricted to batch learning. Unlike traditional batch learning methods, online learning represents a promising family of efficient and scalable machine learning algorithms for large-scale applications. Most existing studies of online learning require accessing all the attributes/features of training instances. Such a classical setting is not always appropriate for real-world applications when data instances are of high dimensionality or it is expensive to acquire the full set of attributes/features. To address this limitation, we investigate the problem of Online Feature Selection (OFS) in which an online learner is only allowed to maintain a classifier involved only a small and fixed number of features. The key challenge of Online Feature Selection is how to make accurate prediction using a small and fixed number of active features. This is in contrast to the classical setup of online learning where all the features can be used for prediction. We attempt to tackle this challenge by studying sparsity regularization and truncation techniques. Specifically, this article addresses two different tasks of online feature selection: (1) learning with full input where an learner is allowed to access all the features to decide the subset of active features, and (2) learning with partial input where only a limited number of features is allowed to be accessed for each instance by the learner. We present novel algorithms to solve each of the two problems and give their performance analysis. We evaluate the performance of the proposed algorithms for online feature selection on several public datasets, and demonstrate their applications to real-world problems including image classification in computer vision and microarray gene expression analysis in bioinformatics. The encouraging results of our experiments validate the efficacy and efficiency of the proposed techniques.Related Publication: Hoi, S. C., Wang, J., Zhao, P., & Jin, R. (2012). Online feature selection for mining big data. In <em>Proceedings of the 1st International Workshop on Big Data, Streams and Heterogeneous Source Mining: Algorithms, Systems, Programming Models and Applications</em> (pp. 93-100). ACM. http://dx.doi.org/10.1145/2351316.2351329 Full text available in InK: http://ink.library.smu.edu.sg/sis_research/2402/ Wang, J., Zhao, P., Hoi, S. C., & Jin, R. (2014). Online feature selection and its applications. IEEE Transactions on Knowledge and Data Engineering, 26(3), 698-710. http://dx.doi.org/10.1109/TKDE.2013.32 Full text available in InK: http://ink.library.smu.edu.sg/sis_research/2277/
DOI: 10.25440/smu.12062733.v1
title: Online Feature Selection and Its Applications

description: Feature selection is an important technique for data mining before a machine learning algorithm is applied. Despite its importance, most studies of feature selection are restricted to batch learning. Unlike traditional batch learning methods, online learning represents a promising family of efficient and scalable machine learning algorithms for large-scale applications. Most existing studies of online learning require accessing all the attributes/features of training instances. Such a classical setting is not always appropriate for real-world applications when data instances are of high dimensionality or it is expensive to acquire the full set of attributes/features. To address this limitation, we investigate the problem of Online Feature Selection (OFS) in which an online learner is only allowed to maintain a classifier involved only a small and fixed number of features. The key challenge of Online Feature Selection is how to make accurate prediction using a small and fixed number of active features. This is in contrast to the classical setup of online learning where all the features can be used for prediction. We attempt to tackle this challenge by studying sparsity regularization and truncation techniques. Specifically, this article addresses two different tasks of online feature selection: (1) learning with full input where an learner is allowed to access all the features to decide the subset of active features, and (2) learning with partial input where only a limited number of features is allowed to be accessed for each instance by the learner. We present novel algorithms to solve each of the two problems and give their performance analysis. We evaluate the performance of the proposed algorithms for online feature selection on several public datasets, and demonstrate their applications to real-world problems including image classification in computer vision and microarray gene expression analysis in bioinformatics. The encouraging results of our experiments validate the efficacy and efficiency of the proposed techniques.Related Publication: Hoi, S. C., Wang, J., Zhao, P., & Jin, R. (2012). Online feature selection for mining big data. In <em>Proceedings of the 1st International Workshop on Big Data, Streams and Heterogeneous Source Mining: Algorithms, Systems, Programming Models and Applications</em> (pp. 93-100). ACM. http://dx.doi.org/10.1145/2351316.2351329 Full text available in InK: http://ink.library.smu.edu.sg/sis_research/2402/ Wang, J., Zhao, P., Hoi, S. C., & Jin, R. (2014). Online feature selection and its applications. IEEE Transactions on Knowledge and Data Engineering, 26(3), 698-710. http://dx.doi.org/10.1109/TKDE.2013.32 Full text available in InK: http://ink.library.smu.edu.sg/sis_research/2277/
DOI: 10.25721/by4p-zm30
title: Charbonnier mon ami, o gué
DOI: 10.25440/smu.12062739
title: Library for Online Learning Algorithms (LIBOL)

description: LIBOL is an open-source machine learning library that consists of a family of classical and state-of-the-art online learning algorithms for large-scale machine learning and data mining research. It includes two categories of online learning methods: regular linear online learning algorithms and kernel-based online learning algorithms.Related Publication: Hoi, S. C. H., Wang, J., & Zhao, P. (2014). LIBOL: A library for online learning algorithms. <em>Journal of Machine Learning Research, 15</em> (1), 495-499. http://jmlr.org/papers/v15/hoi14a.html
DOI: 10.25440/smu.12062739.v1
title: Library for Online Learning Algorithms (LIBOL)

description: LIBOL is an open-source machine learning library that consists of a family of classical and state-of-the-art online learning algorithms for large-scale machine learning and data mining research. It includes two categories of online learning methods: regular linear online learning algorithms and kernel-based online learning algorithms.Related Publication: Hoi, S. C. H., Wang, J., & Zhao, P. (2014). LIBOL: A library for online learning algorithms. <em>Journal of Machine Learning Research, 15</em> (1), 495-499. http://jmlr.org/papers/v15/hoi14a.html
DOI: 10.25721/4g73-7b88
title: Quand j'étais chez mon père garçon à marier
DOI: 10.25721/4f9s-pn30
title: Les jeunes filles de Saint-Quay
DOI: 10.25721/f7xb-dg05
title: Les rochers de Saint-Louis
DOI: 10.25721/b54j-rc78
title: Au bord d'une fontaine
DOI: 10.25721/vn9a-2496
title: Au bord d'une fontaine
DOI: 10.25721/sfjf-r193
title: En voila une pelle blanche avec son joli manche
DOI: 10.25721/r3nv-v467
title: Sur la rivière de Bordeaux
DOI: 10.25721/dkyg-3s51
title: Père Couturier
DOI: 10.25721/yb24-c910
title: Allons pêcheurs de Bretagne
DOI: 10.25721/ckze-3692
title: En voila une pelle blanche avec son joli manche
DOI: 10.25721/m4yb-qx17
title: Les filles de Saint-Pierre
DOI: 10.25721/krc9-az51
title: Connais-tu "Hâte ta patte"
DOI: 10.25721/f69q-nd23
title: Sont les filles de la Rochelle
DOI: 10.25721/pf26-hb50
title: La petite Agathe
DOI: 10.25721/sxgx-eq08
title: Dans les faubourgs de Nantes
DOI: 10.25440/smu.12062742
title: Online Portfolio Selection Toolbox

description: OLPS is an open-source toolbox for On-Line Portfolio Selection, which includes a collection of classical and state-of-the-art on-line portofolio selection strategies implemented in Matlab/Octave.Related Publication: Li, B., & Hoi, S. C. (2014). Online portfolio selection: A survey. <em>ACM Computing Surveys</em>, <em>46</em>(3), 35. http://doi.org/10.1145/2512962
DOI: 10.25440/smu.12062742.v1
title: Online Portfolio Selection Toolbox

description: OLPS is an open-source toolbox for On-Line Portfolio Selection, which includes a collection of classical and state-of-the-art on-line portofolio selection strategies implemented in Matlab/Octave.Related Publication: Li, B., & Hoi, S. C. (2014). Online portfolio selection: A survey. <em>ACM Computing Surveys</em>, <em>46</em>(3), 35. http://doi.org/10.1145/2512962
DOI: 10.25721/4bv4-7r87
title: Pelle blanche
DOI: 10.25721/sdka-fg66
title: J'ai la gorge sèche
DOI: 10.25721/w16r-1662
title: Ceux qui ont nommé les Bancs
DOI: 10.25721/bcmk-kn40
title: Ah ! la belle campagne du banc
DOI: 10.25721/7chb-zm98
title: Pique la baleine
DOI: 10.25721/rs7j-8075
title: Le 31 du mois d'août
DOI: 10.25721/x6c8-w805
title: Jean-François de Nantes
DOI: 10.25440/smu.12062745.v1
title: Data from: Improve Space and Manpower Utilisation

description: The Excel file included the data collected on the space and manpower utilisation for the seat hogging problem in the [Li Ka Shing] Library over the period February to March 2015. The analysis done included, Cause and Effect, Failure Modes and Effects Analysis, Multiple Variables, Pugh Matrix, etc. Poster abstract: From weeks 11 to 14, the [Li Ka Shing] Library sees a surge in the percentage of hogged seats to up to 31% of its capacity, which diverts manpower from its main operations to deal with both the problem and complaints from users that ensure. The team looked for a solution to decrease the percentage of hogged seats by creating a seat-hog free zone for users.Related Publication: Lau, Aldred, Tan, Eileen, Lee, Jo Xin, Lim, Joshua, Lee, Shu Wei, et al. (2015, April). Improve Space and Manpower Utilisation. Poster presented at Singapore Management University, Singapore. http://ink.library.smu.edu.sg/library_research/55/
DOI: 10.25721/vkrv-a536
title: Chantons pour passer le temps
DOI: 10.25721/tyvk-rc22
title: Manoeuvre pour hisser le grand foc, commandement
DOI: 10.25440/smu.12062745
title: Data from: Improve Space and Manpower Utilisation

description: The Excel file included the data collected on the space and manpower utilisation for the seat hogging problem in the [Li Ka Shing] Library over the period February to March 2015. The analysis done included, Cause and Effect, Failure Modes and Effects Analysis, Multiple Variables, Pugh Matrix, etc. Poster abstract: From weeks 11 to 14, the [Li Ka Shing] Library sees a surge in the percentage of hogged seats to up to 31% of its capacity, which diverts manpower from its main operations to deal with both the problem and complaints from users that ensure. The team looked for a solution to decrease the percentage of hogged seats by creating a seat-hog free zone for users.Related Publication: Lau, Aldred, Tan, Eileen, Lee, Jo Xin, Lim, Joshua, Lee, Shu Wei, et al. (2015, April). Improve Space and Manpower Utilisation. Poster presented at Singapore Management University, Singapore. http://ink.library.smu.edu.sg/library_research/55/
DOI: 10.25721/rm89-hp68
title: Manoeuvre pour hisser le grand foc, commandement
DOI: 10.25721/e1hq-v196
title: Marie-Margot vient de tomber
DOI: 10.25721/ttm4-ec02
title: Marie-Margot sur son balcon
DOI: 10.25721/ebjj-dg42
title: La Danaé
DOI: 10.25721/vvz8-gv87
title: Prière à Neptune
DOI: 10.25721/v4xw-1c93
title: Autobiographie de Monsieur Yves Bellec
DOI: 10.25440/smu.12062754
title: Data from: Worker selection, hiring, and vacancies

description: This record contains the underlying research data for the publication "Worker selection, hiring, and vacancies" and the full-text is available from: https://ink.library.smu.edu.sg/soe_research/1990The ratio of hirings to vacancies in the U.S. has the following establishment level properties: (i) it steeply rises with employment growth rate; (ii) falls with establishment size; and (iii) rises with worker turnover rate. The standard Diamond-Mortensen Pissarides (DMP) matching model is not compatible with these observations. This paper augments selection of workers prior to hiring into a random matching model with multi-worker ﬁrms. In the calibrated model, worker selection accounts for about 30% of the variation in the hiring-vacancy ratio observed in the data. Compared to the standard model, the worker selection model has both qualitative and quantitative policy implications. A hiring subsidy reduces the unemployment rate substantially in the worker selection model, whereas the reduction in the unemployment rate is very small in the standard model. The two models also diﬀer regarding the impact of the hiring subsidy across ﬁrms. The worker selection model implies that ﬁrms that have initially high worker turnover rates experience proportionally higher worker turnover rates after the subsidy. In contrast, the standard model predicts that the worker turnover rate increases proportionally more at ﬁrms with initially lower worker turnover rates.<br>
DOI: 10.25721/raz5-pf30
title: Je m'en vais à la promenade
DOI: 10.25440/smu.12062754.v1
title: Data from: Worker selection, hiring, and vacancies

description: This record contains the underlying research data for the publication "Worker selection, hiring, and vacancies" and the full-text is available from: https://ink.library.smu.edu.sg/soe_research/1990The ratio of hirings to vacancies in the U.S. has the following establishment level properties: (i) it steeply rises with employment growth rate; (ii) falls with establishment size; and (iii) rises with worker turnover rate. The standard Diamond-Mortensen Pissarides (DMP) matching model is not compatible with these observations. This paper augments selection of workers prior to hiring into a random matching model with multi-worker ﬁrms. In the calibrated model, worker selection accounts for about 30% of the variation in the hiring-vacancy ratio observed in the data. Compared to the standard model, the worker selection model has both qualitative and quantitative policy implications. A hiring subsidy reduces the unemployment rate substantially in the worker selection model, whereas the reduction in the unemployment rate is very small in the standard model. The two models also diﬀer regarding the impact of the hiring subsidy across ﬁrms. The worker selection model implies that ﬁrms that have initially high worker turnover rates experience proportionally higher worker turnover rates after the subsidy. In contrast, the standard model predicts that the worker turnover rate increases proportionally more at ﬁrms with initially lower worker turnover rates.<br>
DOI: 10.25721/0p1x-0684
title: Information sur la vie des marchands d'oignons
DOI: 10.25440/smu.12062757
title: Data from: Estimating the reproducibility of psychological science

description: This record contains the underlying research data for the publication "Estimating the reproducibility of psychological science" and the full-text is available from: https://ink.library.smu.edu.sg/lkcsb_research/5257Reproducibility is a defining feature of science, but the extent to which it characterizes current research is unknown. We conducted replications of 100 experimental and correlational studies published in three psychology journals using high-powered designs and original materials when available. Replication effects were half the magnitude of original effects, representing a substantial decline. Ninety-seven percent of original studies had statistically significant results. Thirty-six percent of replications had statistically significant results; 47% of original effect sizes were in the 95% confidence interval of the replication effect size; 39% of effects were subjectively rated to have replicated the original result; and if no bias in original results is assumed, combining original and replication results left 68% with statistically significant effects. Correlational tests suggest that replication success was better predicted by the strength of original evidence than by characteristics of the original and replication teams.
DOI: 10.25721/c1gx-cm53
title: Information sur la chanson "Julianig" (Petite Julienne)
DOI: 10.25440/smu.12062757.v1
title: Data from: Estimating the reproducibility of psychological science

description: This record contains the underlying research data for the publication "Estimating the reproducibility of psychological science" and the full-text is available from: https://ink.library.smu.edu.sg/lkcsb_research/5257Reproducibility is a defining feature of science, but the extent to which it characterizes current research is unknown. We conducted replications of 100 experimental and correlational studies published in three psychology journals using high-powered designs and original materials when available. Replication effects were half the magnitude of original effects, representing a substantial decline. Ninety-seven percent of original studies had statistically significant results. Thirty-six percent of replications had statistically significant results; 47% of original effect sizes were in the 95% confidence interval of the replication effect size; 39% of effects were subjectively rated to have replicated the original result; and if no bias in original results is assumed, combining original and replication results left 68% with statistically significant effects. Correlational tests suggest that replication success was better predicted by the strength of original evidence than by characteristics of the original and replication teams.
DOI: 10.25721/4tzc-9169
title: Information sur la chanson "Teodou fall" (Les mauvaises langues), enregistrée sur la bande magnétique MUS1953.7.11
DOI: 10.25721/9mx1-7a09
title: Information sur la chanson "Ar Vengeur" (Le vengeur)
DOI: 10.25721/jdp9-cw18
title: Information
DOI: 10.25721/y72w-ny20
title: Information sur la chanson "Den brao"
DOI: 10.25721/n3cw-k181
title: Information sur la chanson "Sylvestrig", enregistrée sur la bande magnétique MUS1953.7.12
DOI: 10.25721/j0n1-t234
title: Information sur le cantique de Sainte Anne, enregistrée sur la bande magnétique MUS1953.7.19
DOI: 10.25721/gmk2-tt96
title: Information sur le cantique de Sainte Anne, enregistrée sur la bande magnétique MUS1953.7.19
DOI: 10.25440/smu.12062760.v1
title: Data from: Sidestepping the rock and the hard place: The private avoidance of prosocial requests

description: This record contains the underlying research data for the publication "Sidestepping the rock and the hard place: The private avoidance of prosocial requests" and the full-text is available from: https://ink.library.smu.edu.sg/lkcsb_research/5260For some, facing a prosocial request feels like being trapped between a rock and a hard place, requiring either a resource (e.g., money) or psychological (e.g., self-reproach) cost. Because both outcomes are dissatisfying, we propose that these people are motivated to avoid prosocial requests, even when they face these requests in private, anonymous contexts. In two experiments, in which participants' anonymity and privacy was assured, participants avoided facing prosocial requests and were willing to do so at a personal cost. This was true both for people who would have otherwise complied with the request and those who would have otherwise refused the request. This suggests that anticipatory self-reproach motivates people to avoid prosocial requests, regardless of whether or not this self-reproach would have been strong enough to cause them to comply with a direct request. We discuss the theoretical and practical implications of these findings for prosocial behavior and the maintenance of moral self-regard.
DOI: 10.25721/pxjr-qg65
title: Une petite négresse
DOI: 10.25721/sxw8-7d07
title: Le condamné
DOI: 10.25440/smu.12062760
title: Data from: Sidestepping the rock and the hard place: The private avoidance of prosocial requests

description: This record contains the underlying research data for the publication "Sidestepping the rock and the hard place: The private avoidance of prosocial requests" and the full-text is available from: https://ink.library.smu.edu.sg/lkcsb_research/5260For some, facing a prosocial request feels like being trapped between a rock and a hard place, requiring either a resource (e.g., money) or psychological (e.g., self-reproach) cost. Because both outcomes are dissatisfying, we propose that these people are motivated to avoid prosocial requests, even when they face these requests in private, anonymous contexts. In two experiments, in which participants' anonymity and privacy was assured, participants avoided facing prosocial requests and were willing to do so at a personal cost. This was true both for people who would have otherwise complied with the request and those who would have otherwise refused the request. This suggests that anticipatory self-reproach motivates people to avoid prosocial requests, regardless of whether or not this self-reproach would have been strong enough to cause them to comply with a direct request. We discuss the theoretical and practical implications of these findings for prosocial behavior and the maintenance of moral self-regard.
DOI: 10.25721/fz46-dp82
title: Information sur les feux de la Saint Jean et de Sainte Anne
DOI: 10.25721/7w4b-wt57
title: Autobiographie de Monsieur Raymond Dirou
DOI: 10.25721/gxha-7n78
title: La petite diligence
DOI: 10.25721/w8g5-cz95
title: Information sur la chanson "Ar pilhaouer", enregistrée sur la bande magnétique MUS1953.7.27
DOI: 10.25721/f055-xf20
title: Information sur la chanson : "Eisté goude an ewred me"
DOI: 10.25721/2h9z-e520
title: Information sur la chanson : "Eul louarnig yaouank"
DOI: 10.25721/ybp2-bv98
title: Information sur la chanson : "P'edon war bond an Naoned"
DOI: 10.25721/kn15-z855
title: Information sur la chanson : "Eur minor eus ar géar-man"
DOI: 10.25721/ck7s-w258
title: Information sur la chanson : "Pantalon blanc, chemise de service"
DOI: 10.25721/b6n1-9m07
title: Information sur la chanson : "Merc'hédou Nokenolé"
DOI: 10.25721/0y4j-4160
title: Information sur la chanson : "Petra durzunell yaouank"
DOI: 10.25721/s8bt-1g28
title: Information sur la chanson : "Diouz an noz hag ar mintin"
DOI: 10.25721/df46-x246
title: Information sur la chanson : "Le juif errant"
DOI: 10.25721/vjz3-1640
title: Information sur la prière "Spered Santel benniget"
DOI: 10.25721/jgac-7558
title: Information sur la prière "Bonjour ma petite Jeannette"