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Mixture model
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161	Distributed and Adaptive Darting Monte Carlo through Regenerations Sungjin Ahn Department of Computer Science University of California, Irvine Irvine, CA, USA Add to Reading List Source URL: www.ics.uci.edu Language: English - Date: 2013-04-11 10:50:54 Markov models Markov chain Monte Carlo Computational statistics Markov processes Markov chain Metropolis–Hastings algorithm Rejection sampling Mixture model Random walk Statistics Probability and statistics Monte Carlo methods
162	An Alternative Prior Process for Nonparametric Bayesian Clustering Hanna M. Wallach Department of Computer Science University of Massachusetts Amherst Add to Reading List Source URL: www.gatsby.ucl.ac.uk Language: English - Date: 2010-03-15 18:50:30 Pitman–Yor process Chinese restaurant process Dirichlet distribution Concentration parameter Mixture model Bayesian inference Prior probability Statistics Stochastic processes Dirichlet process
163	Bayesian Learning via Stochastic Gradient Langevin Dynamics Add to Reading List Source URL: www.ics.uci.edu Language: English - Date: 2011-05-21 11:48:52 Computational statistics Stochastic optimization Statistical mechanics Estimation theory Markov chain Monte Carlo Langevin dynamics Stochastic approximation Metropolis–Hastings algorithm Mixture model Statistics Probability and statistics Monte Carlo methods
164	Infinite State Bayesian Networks Max Welling∗, Ian Porteous, Evgeniy Bart† Donald Bren School of Information and Computer Sciences University of California Irvine Irvine, CAUSA {welling,iporteou}@ics.uci. Add to Reading List Source URL: www.ics.uci.edu Language: English - Date: 2008-01-10 04:29:00 Statistical natural language processing Markov models Graphical models Variational Bayesian methods Dirichlet process Gibbs sampling Bayesian network Latent Dirichlet allocation Mixture model Statistics Bayesian statistics Statistical models
165	INSTITUT NATIONAL DE RECHERCHE EN INFORMATIQUE ET EN AUTOMATIQUE Project-Team mistis Modelling and Inference of Complex and Structured Stochastic Systems Grenoble - Rhône-Alpes Add to Reading List Source URL: mistis.inrialpes.fr Language: English - Date: 2014-09-23 04:38:29 Machine learning Markov models Robust statistics Mixture model Non-parametric statistics Markov chain Parametric statistics Hidden Markov model Regression analysis Statistics Statistical inference Statistical models
166	Journal of Machine Learning Research xx-xx Submitted 6/08; Published xx/xx Distributed Algorithms for Topic Models David Newman Add to Reading List Source URL: www.ics.uci.edu Language: English - Date: 2009-09-08 17:03:36 Latent Dirichlet allocation Statistical classification Bayesian networks Topic model Mixture model Dirichlet process Linear discriminant analysis Algorithm Gibbs sampling Statistics Statistical natural language processing Statistical models
167	Bayesian K-Means as a “Maximization-Expectation” Algorithm October 18, 2007 Abstract Add to Reading List Source URL: www.ics.uci.edu Language: English - Date: 2007-10-18 14:00:50 Statistical theory Expectation–maximization algorithm Missing data Statistical models Maximum likelihood Fisher information Variational Bayesian methods Marginal likelihood Mixture model Statistics Estimation theory Bayesian statistics
168	Bayesian Hierarchical Clustering Katherine A. Heller Zoubin Ghahramani Gatsby Computational Neuroscience Unit, University College London 17 Queen Square, London, WC1N 3AR, UK Add to Reading List Source URL: www.gatsby.ucl.ac.uk Language: English - Date: 2007-01-29 12:58:00 Cluster analysis Bioinformatics Data mining Hierarchical clustering Single-linkage clustering Conjugate prior Mixture model Dirichlet process Variational Bayesian methods Statistics Machine learning Bayesian statistics
169	DiscLDA: Discriminative Learning for Dimensionality Reduction and Classification Simon Lacoste-Julien Computer Science Division UC Berkeley Add to Reading List Source URL: www.cs.berkeley.edu Language: English - Date: 2009-01-10 00:13:43 Statistical classification Statistical models Information retrieval Latent Dirichlet allocation Linear discriminant analysis Probabilistic latent semantic analysis Mixture model Topic model Maximum likelihood Statistics Statistical natural language processing Machine learning
170	Probabilistic Classification of Image Regions using Unsupervised and Supervised Learning Add to Reading List Source URL: www.sanjivk.com Language: English - Date: 2010-06-01 18:49:42 Pattern recognition Segmentation Mixture model Minimum description length Generative model Unsupervised learning Expectation–maximization algorithm Statistical classification Supervised learning Statistics Machine learning Cluster analysis

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