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Statistical learning theory
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#	Item
131	On Agreement and Learning∗ Elchanan Mossel†, Allan Sly‡and Omer Tamuz§ arXiv:1207.5895v1 [math.ST] 25 JulJuly 26, 2012 Add to Reading List Source URL: people.hss.caltech.edu Language: English - Date: 2012-07-27 05:59:55 Game theory Bayesian statistics Statistical inference Statistical theory Probability and statistics Bayesian game Bayesian inference Posterior probability Probability Conditional independence Common knowledge Bayesian network
132	How do you know that? Sensitivity to statistical dependency in social learning Andrew Whalen () Daphna Buchsbaum () Thomas L. Griffiths (tom ) Department of Psyc Add to Reading List Source URL: cocosci.berkeley.edu Language: English - Date: 2013-05-02 18:42:13 Statistics Statistical theory Statistical inference Information Knowledge Probability and statistics Bayesian statistics Behavioral finance Information cascade Informant Probability Bayesian inference
133	BPR: Bayesian Personalized Ranking from Implicit Feedback Steffen Rendle, Christoph Freudenthaler, Zeno Gantner and Lars Schmidt-Thieme {srendle, freudenthaler, gantner, schmidt-thieme}@ismll.de Machine Learning Lab, Un Add to Reading List Source URL: www.algo.uni-konstanz.de Language: English - Date: 2015-07-15 09:56:07 Algebra Mathematics Information science Linear algebra Matrix theory Recommender systems Statistical theory Collaborative filtering Machine learning Loss function Singular value decomposition Artificial neural network
134	Journal of Machine Learning Research–1959 Submitted 10/05; PublishedA Unifying View of Sparse Approximate Gaussian Process Regression Add to Reading List Source URL: jmlr.org Language: English - Date: 2005-12-15 14:17:11 Mathematical analysis Statistical theory Probability theory Normal distribution Stable distributions Multivariate normal distribution Regression analysis Gaussian process Kalman filter
135	INTRODUCTION TO MACHINE LEARNING AN EARLY DRAFT OF A PROPOSED TEXTBOOK Add to Reading List Source URL: robotics.stanford.edu Language: English - Date: 2010-06-21 13:24:18 Learning Machine learning Education Cognition Artificial neural networks Educational psychology Computational neuroscience Computational statistics Supervised learning Computational learning theory Backpropagation Statistical learning theory
136	Evidence-Specific Structures for Rich Tractable CRFs Carlos Guestrin Carnegie Mellon University Add to Reading List Source URL: select.cs.cmu.edu Language: English - Date: 2010-12-02 01:46:24 Graph theory Graphical models Machine learning Artificial intelligence Learning Statistical models Conditional random field Bayesian network Tree decomposition Treewidth Markov random field Expectationmaximization algorithm
137	The Annals of Applied Statistics 2014, Vol. 8, No. 3, 1750–1781 DOI: AOAS755 © Institute of Mathematical Statistics, 2014 VARIABLE SELECTION FOR BART: AN APPLICATION Add to Reading List Source URL: www-stat.wharton.upenn.edu Language: English - Date: 2015-10-29 18:32:57 Statistics Statistical inference Estimation theory Regression analysis Nonparametric regression Linear regression Machine learning Stepwise regression Decision tree learning Spike-and-slab variable selection Omnibus test
138	Journal of Experimental Psychology: Learning, Memory, and Cognition 2013, Vol. 39, No. 5, 1473–1490 © 2013 American Psychological Association/$12.00 DOI: a0032397 Add to Reading List Source URL: cocosci.berkeley.edu Language: English - Date: 2015-10-08 17:16:50 Randomness Design of experiments Hypothesis testing Statistical randomness Statistical theory Fair coin Random sequence Likelihood-ratio test Random variable Statistical hypothesis testing Statistics Type I and type II errors
139	Forum Probabilistic models, learning algorithms, and response variability: sampling in cognitive development Elizabeth Bonawitz1, Stephanie Denison2, Thomas L. Griffiths3, and Alison Gopnik3 Add to Reading List Source URL: ccdlab.rutgers.edu Language: English - Date: 2015-09-25 18:39:53 Statistical inference Statistical theory Philosophy of science Sampling techniques Psychometrics Bayesian inference Statistics Monte Carlo method Statistical hypothesis testing Sampling Causality Bayesian network
140	Learning Policies for Contextual Submodular Prediction Stephane Ross Jiaji Zhou Yisong Yue Debadeepta Dey Add to Reading List Source URL: select.cs.cmu.edu Language: English Submodular set function Automatic summarization Statistical classification Number theory Support vector machine Machine learning Reinforcement learning Mathematical optimization Distribution

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