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Mixture model
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#	Item
511	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
512	Combining Mixture Components for Clustering Add to Reading List Source URL: www.stat.washington.edu Language: English - Date: 2011-05-24 20:39:20 Mixture model Hierarchical clustering Computer cluster Entropy Expectation–maximization algorithm Determining the number of clusters in a data set Statistics Cluster analysis Machine learning
513	Continuous Time Group Discovery in Dynamic Graphs Tina Eliassi-Rad2 [removed] Add to Reading List Source URL: snap.stanford.edu Language: English - Date: 2009-11-25 18:32:54 Latent Dirichlet allocation Dynamic topic model Topic model Mixture model Dirichlet distribution Multinomial distribution Statistics Statistical natural language processing Probability and statistics
514	Scaling Nonparametric Bayesian Inference via Subsample-Annealing arXiv:1402.5473v1 [stat.ML] 22 Feb[removed]Fritz Obermeyer Add to Reading List Source URL: arxiv.org Language: English - Date: 2014-02-24 20:28:21 Computational statistics Markov models Estimation theory Statistical inference Gibbs sampling Hidden Markov model Simulated annealing Mixture model Bayesian inference Statistics Probability and statistics Monte Carlo methods
515	Modeling corpora of timestamped documents using semisupervised nonparametric topic models William W. Cohen Machine Learning Department Carnegie Mellon University Add to Reading List Source URL: www.cs.cmu.edu Language: English - Date: 2009-06-10 16:21:26 Markov models Dirichlet process Latent Dirichlet allocation Mixture model Topic model Perplexity Markov chain Non-parametric statistics Timestamp Statistics Statistical natural language processing Stochastic processes
516	REVISITING SEMI-CONTINUOUS HIDDEN MARKOV MODELS K. Riedhammer1 , T. Bocklet1 , A. Ghoshal2,3 , D. Povey4 1 Pattern Recognition Lab, University of Erlangen-Nuremberg, G ERMANY 2 Add to Reading List Source URL: homepages.inf.ed.ac.uk Language: English - Date: 2012-06-12 09:45:08 Probability and statistics Estimation theory Markov models Bioinformatics Hidden Markov model Mixture model Speech recognition Expectation–maximization algorithm Pattern recognition Statistics Machine learning Computational statistics
517	3 Semi-Supervised Text Classification Using EM Kamal Nigam Andrew McCallum Tom Mitchell Add to Reading List Source URL: www.cs.cmu.edu Language: English - Date: 2006-03-07 20:47:10 Supervised learning Naive Bayes classifier Co-training Mixture model Document classification Generative model Expectation–maximization algorithm Statistical classification Maximum likelihood Statistics Machine learning Semi-supervised learning
518	Hidden Markov Models A Tutorial for the Course Computational Intelligence http://www.igi.tugraz.at/lehre/CI Barbara Resch (modified by Erhard and Car line Rank) Signal Processing and Speech Communication Laboratory Add to Reading List Source URL: speech.tifr.res.in Language: English - Date: 2014-08-07 09:12:45 Machine learning Hidden Markov model Forward–backward algorithm Markov chain Viterbi algorithm Maximum likelihood Markov property Likelihood function Mixture model Statistics Markov models Probability and statistics
519	Background Subtraction on Distributions Teresa Ko, Stefano Soatto, and Deborah Estrin Vision Lab Computer Science Department University of California, Los Angeles 405 Hilgard Avenue, Los Angeles – CA 90095 Add to Reading List Source URL: vision.ucla.edu Language: English - Date: 2008-08-28 23:50:23 Segmentation Normal distribution Mixture model Pixel Image processing Statistics Probability
520	Ann Inst Stat Math[removed]:11–35 DOI[removed]s10463[removed]Latent class analysis variable selection Nema Dean · Adrian E. Raftery Add to Reading List Source URL: www.stat.washington.edu Language: English - Date: 2010-06-07 17:10:09 Model selection Categorical data Regression analysis Expectation–maximization algorithm Latent class model Bayesian information criterion Mixture model Feature selection Maximum likelihood Statistics Statistical models Estimation theory

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