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Variational Bayesian methods
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#	Item
111	Shared Logistic Normal Distributions for Soft Parameter Tying in Unsupervised Grammar Induction Shay B. Cohen and Noah A. Smith Language Technologies Institute School of Computer Science Carnegie Mellon University Add to Reading List Source URL: www.cs.cmu.edu Language: English - Date: 2009-03-31 16:28:07 Estimation theory Bayesian statistics Statistical theory Bioinformatics Expectation–maximization algorithm Variational Bayesian methods Gamma distribution Multinomial distribution Dirichlet distribution Statistics Probability and statistics Statistical natural language processing
112	On Smoothing and Inference for Topic Models Arthur Asuncion, Max Welling, Padhraic Smyth Department of Computer Science University of California, Irvine Irvine, CA, USA Add to Reading List Source URL: www.ics.uci.edu Language: English - Date: 2009-05-27 03:06:42 Variational Bayesian methods Latent Dirichlet allocation Expectation–maximization algorithm Probabilistic latent semantic analysis Dirichlet distribution Bayesian inference Hyperparameter Statistics Bayesian statistics Statistical natural language processing
113	Performance of Bayesian Model Selection Criteria for Gaussian Mixture Models 1 Russell J. Steele McGill University Adrian E. Raftery Add to Reading List Source URL: www.stat.washington.edu Language: English - Date: 2009-09-18 15:00:15 Statistical theory Model selection Bayesian inference Akaike information criterion Conjugate prior Variational Bayesian methods Mixture model Normal distribution Maximum likelihood Statistics Bayesian statistics Estimation theory
114	Expectation propagation as a way of life∗ Andrew Gelman† Aki Vehtari‡ Pasi Jylänki§ Add to Reading List Source URL: www.stat.columbia.edu Language: English - Date: 2014-12-15 22:49:33 Statistical theory Statistical inference Normal distribution Variational Bayesian methods Golden ratio Likelihood function Bayesian inference Expectation–maximization algorithm Empirical Bayes method Statistics Bayesian statistics Estimation theory
115	Incremental Learning of Nonparametric Bayesian Mixture Models Ryan Gomes∗ Max Welling† ∗ Add to Reading List Source URL: www.ics.uci.edu Language: English - Date: 2008-04-09 01:39:03 Cluster analysis Data analysis Estimation theory Expectation–maximization algorithm Dirichlet process Variational Bayesian methods Mixture model Principal component analysis Kernel principal component analysis Statistics Multivariate statistics Machine learning
116	ECAI 2014 T. Schaub et al. (Eds.) © 2014 The Authors and IOS Press. This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial Licen Add to Reading List Source URL: users.ics.aalto.fi Language: English - Date: 2014-08-03 02:46:45 Multivariate statistics Singular value decomposition Linear algebra Numerical linear algebra Principal component analysis Conjugate prior Variational Bayesian methods Normal distribution Multivariate normal distribution Statistics Algebra Bayesian statistics
117	On the Design and Quantification of Privacy Preserving Data Mining Algorithms Dakshi Agrawal Charu C. Aggarwal Add to Reading List Source URL: www.charuaggarwal.net Language: English - Date: 2006-11-17 15:35:44 Statistical theory Expectation–maximization algorithm Missing data Normal distribution Mutual information Logarithm Entropy Maximum likelihood Variational Bayesian methods Statistics Estimation theory Information theory
118	Fully Automatic Variational Inference of Differentiable Probability Models Rajesh Ranganath Department of Computer Science Princeton University Add to Reading List Source URL: andrewgelman.com Language: English - Date: 2014-12-21 20:40:21 Econometrics Estimation theory Variational Bayesian methods Bayesian linear regression Multivariate normal distribution Linear regression Mathematical optimization Expectation–maximization algorithm Variational message passing Statistics Bayesian statistics Regression analysis
119	Stochastic Backpropagation and Approximate Inference in Deep Generative Models arXiv:1401.4082v3 [stat.ML] 30 May[removed]Danilo J. Rezende, Shakir Mohamed, Daan Wierstra Add to Reading List Source URL: arxiv.org Language: English - Date: 2014-06-01 20:20:02 Bayesian statistics Machine learning Statistical theory Variational Bayesian methods Backpropagation Gaussian process Bayesian network Perceptron Generative model Statistics Neural networks Statistical models
120	Neural Variational Inference and Learning in Belief Networks Add to Reading List Source URL: arxiv.org Language: English - Date: 2014-06-04 22:03:38 Neural networks Computational neuroscience Graphical models Variational Bayesian methods Bayesian network Boltzmann machine Machine learning Bayesian inference Expectation–maximization algorithm Statistics Bayesian statistics Networks

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