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Statistical learning theory
Results: 800

#	Item
561	Supplementary material: One-shot learning by inverting a compositional causal process SI-1 Generating images of characters Add to Reading List Source URL: www.cs.toronto.edu Language: English - Date: 2013-11-19 21:15:24 M-estimators Econometrics Measurement Maximum likelihood Generalized method of moments Dimensional analysis Estimation theory Statistics Statistical theory
562	Journal of Machine Learning Research[removed]1347 Submitted 6/12; Published 5/13 Stochastic Variational Inference Matthew D. Hoffman Add to Reading List Source URL: www.cs.princeton.edu Language: English - Date: 2013-06-14 05:31:44 Estimation theory Econometrics Statistical models Expectation–maximization algorithm Mixture model Markov chain Linear regression Latent Dirichlet allocation Regression analysis Statistics Bayesian statistics Markov models
563	Journal of Machine Learning Research[removed]2410 Submitted 10/09; Revised 12/10; Published 8/10 Distance Dependent Chinese Restaurant Processes David M. Blei Add to Reading List Source URL: www.cs.princeton.edu Language: English - Date: 2013-02-16 21:04:48 Machine learning Probability theory Dirichlet process Chinese restaurant process Mixture model Cluster analysis Mixture Exchangeable random variables Statistics Stochastic processes Statistical models
564	Learning Stochastic Feedforward Neural Networks Yichuan Tang Department of Computer Science University of Toronto Toronto, Ontario, Canada. Add to Reading List Source URL: www.cs.toronto.edu Language: English - Date: 2013-11-19 21:06:13 Machine learning Estimation theory Statistical theory Expectation–maximization algorithm Bayesian network Gibbs sampling Perceptron Kullback–Leibler divergence Mixture model Statistics Statistical models Neural networks
565	A Bias Correction for the Minimum Error Rate in Cross-validation Ryan J. Tibshirani∗ Robert Tibshirani† Add to Reading List Source URL: www.stat.cmu.edu Language: English - Date: 2013-01-11 01:57:27 Statistical theory Statistical inference Data analysis Cross-validation Bootstrapping Supervised learning M-estimator Gaussian function Loss function Statistics Estimation theory Machine learning
566	Journal of Machine Learning Research[removed]1031 Submitted 9/12; Revised 1/13; Published 4/13 Variational Inference in Nonconjugate Models Chong Wang Add to Reading List Source URL: www.cs.princeton.edu Language: English - Date: 2013-06-14 05:31:44 Estimation theory Gamma distribution Conjugate prior Exponential family Marginal likelihood Delta method Sufficient statistic Kullback–Leibler divergence Expectation–maximization algorithm Statistics Statistical theory Bayesian statistics
567	Domain Adaptation: Learning Bounds and Algorithms Yishay Mansour Google Research and Tel Aviv Univ. Add to Reading List Source URL: www.cs.nyu.edu Language: English - Date: 2009-11-02 10:14:29 Machine learning Information theory Operator theory Kullback–Leibler divergence Thermodynamics Empirical risk minimization Entropy Hilbert space Multivariate normal distribution Statistics Statistical theory Probability and statistics
568	JMLR: Workshop and Conference Proceedings vol[removed]–32 24th Annual Conference on Learning Theory Sample Complexity Bounds for Differentially Private Learning Add to Reading List Source URL: www.cs.columbia.edu Language: English - Date: 2014-11-25 10:45:21 Ethics Artificial intelligence Learning Statistical classification Applied probability Exponential mechanism Differential privacy Empirical risk minimization VC dimension Machine learning Data privacy Statistics
569	Learning Linear Bayesian Networks with Latent Variables Animashree Anandkumar Department of EECS, University of California, Irvine [removed] Add to Reading List Source URL: www.cs.columbia.edu Language: English - Date: 2014-11-25 10:45:20 Graphical models Bayesian statistics Networks Bayesian network Directed acyclic graph Mixture model Latent variable Expectation–maximization algorithm Independent component analysis Statistics Statistical models Estimation theory
570	Two-Stage Learning Kernel Algorithms Corinna Cortes Google Research, 76 Ninth Avenue, New York, NY[removed]CORINNA @ GOOGLE . COM Add to Reading List Source URL: www.cs.nyu.edu Language: English - Date: 2010-05-30 10:30:42 Statistical classification Operator theory Support vector machine Kernel Positive-definite kernel Reproducing kernel Hilbert space Statistics Hilbert space Non-parametric statistics

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