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Machine learning
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#	Item
961	Proceedings Template - WORD Add to Reading List Source URL: www.select.cs.cmu.edu Language: English - Date: 2011-06-25 12:47:15 Humancomputer interaction Recommender systems Social information processing Collective intelligence Personalization Collaborative filtering GroupLens Research Support vector machine News aggregator Machine learning Facebook Automatic summarization
962	Top-N Recommendation with Missing Implicit Feedback Daryl Lim Julian McAuley Gert Lanckriet Add to Reading List Source URL: eceweb.ucsd.edu Language: English - Date: 2015-07-31 19:00:25 Machine learning Psychometrics Information retrieval evaluation Nonparametric statistics Recommender system Precision and recall Learning to rank Missing data Ranking Scale
963	Microsoft Word - LR4IR2009.v4-camera-nomark.doc Add to Reading List Source URL: www.sogou.com Language: English - Date: 2016-06-28 04:30:57 Machine learning Learning Learning to rank Ranking SVM Support vector machine PageRank Ranking Stability Document retrieval Information retrieval Feature selection Supervised learning
964	Microsoft Word - Document1 Add to Reading List Source URL: pars.ie Language: English - Date: 2015-11-01 20:09:33 Computational linguistics Natural language processing SemEval Automatic summarization Semantic network Information extraction Machine translation Text mining Parsing Terminology extraction Ontology learning Treebank
965	Journal of Machine Learning Research2140 Submitted 3/09; Revised 6/10; Published 8/10 Importance Sampling for Continuous Time Bayesian Networks Yu Fan Add to Reading List Source URL: rlair.cs.ucr.edu Language: English - Date: 2011-01-19 19:25:14 Markov models Probability distributions Graphical models Monte Carlo methods Stochastic simulation Bayesian network Markov chain Importance sampling Gibbs sampling Exponential distribution Cumulative distribution function Variance
966	Boosting in the Online Setting Charles Marsh Abstract Boosting in the batch setting is a well-known machine learning technique with strong theoretical foundations and extensive use in practice. In t Add to Reading List Source URL: www.crmarsh.com Language: English - Date: 2016-06-12 18:28:24 Ensemble learning AdaBoost Boosting LPBoost Decision stump K-nearest neighbors algorithm Gradient boosting
967	To appear: IEEE Transactions on Information Forensics and Security Face Recognition Performance: Role of Demographic Information Brendan F. Klare, Member, IEEE, Mark J. Burge, Senior Member, IEEE, Joshua C. Klontz, Rich Add to Reading List Source URL: openbiometrics.org Language: English - Date: 2016-08-02 16:53:35 Face recognition Surveillance Machine learning Feature detection Local binary patterns Facial recognition system Demography of the United States Face detection Biometrics Cohort Statistical classification
968	IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. 21, NO. 5, MAYCo-Transduction for Shape Retrieval Xiang Bai, Bo Wang, Cong Yao, Wenyu Liu, and Zhuowen Tu Add to Reading List Source URL: pages.ucsd.edu Language: English - Date: 2013-06-24 00:20:34 Machine learning Shape context Image retrieval Transduction Information retrieval K-nearest neighbors algorithm Similarity Shape Manifold regularization MPEG-7 Statistical classification
969	arXiv:1506.06726v1 [cs.CL] 22 JunSkip-Thought Vectors Ryan Kiros 1 , Yukun Zhu 1 , Ruslan Salakhutdinov 1,2 , Richard S. Zemel 1,2 Antonio Torralba 3 , Raquel Urtasun 1 , Sanja Fidler 1 Add to Reading List Source URL: arxiv.org Language: English - Date: 2015-06-22 20:32:14 Artificial neural networks Computational linguistics Machine learning Computational neuroscience Semantics Deep learning Semantic similarity Word embedding Word2vec Feature learning Language model Recurrent neural network
970	CURRICULUM VITAE Richard S. Sutton April 2015 Professor, Department of Computing Science, University of Alberta address: Athabasca Hall 2-21, University of Alberta, Edmonton, AB T6G 2E8 Add to Reading List Source URL: webdocs.cs.ualberta.ca Language: English - Date: 2015-04-07 14:18:17 Computational neuroscience Cybernetics Fellows of the American Association for the Advancement of Science Richard S. Sutton Andrew Barto Reinforcement learning Artificial neural network Machine learning Artificial intelligence Dalle Molle Institute for Artificial Intelligence Research Russell Greiner Timo Honkela