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Dirichlet process
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51	Understanding the “Antoniak equation” The equation I call the “Antoniak equation” (due to Antoniak, 1974) computes the probability that N samples from a Dirichlet process with concentration parameter α will draw Add to Reading List Source URL: www.cs.cmu.edu Language: English - Date: 2010-01-30 01:04:48
52	1 Background Subtraction with Dirichlet Process Mixture Models Tom S. F. Haines and Tao Xiang Abstract—Video analysis often begins with background subtraction. This problem is often approached in two steps - a backgro Add to Reading List Source URL: thaines.com Language: English - Date: 2014-10-31 07:18:24
53	Dirichlet Distribution, Dirichlet Process and Dirichlet Process Mixture Leon Gu CSD, CMU Binomial and Multinomial Add to Reading List Source URL: www.cs.cmu.edu Language: English - Date: 2008-04-29 13:03:18
54	Copyright Ó 2007 by the Genetics Society of America DOI: geneticsInference of Population Structure Under a Dirichlet Process Model John P. Huelsenbeck,1 and Peter Andolfatto† Department of Integr Add to Reading List Source URL: genomics.princeton.edu Language: English - Date: 2015-07-01 14:48:39
55	The IBP Compound Dirichlet Process and its Application to Focused Topic Modeling Sinead Williamson Department of Engineering, University of Cambridge, Trumpington Street, Cambridge, UK Add to Reading List Source URL: www.gatsby.ucl.ac.uk Language: English - Date: 2010-05-28 08:22:17
56	Exchangeable Inconsistent Priors for Bayesian Posterior Inference Max Welling Ian Porteous Add to Reading List Source URL: www.ics.uci.edu Language: English - Date: 2012-02-01 15:33:24 Dirichlet process Poisson distribution Principle of maximum entropy Prior probability Normal distribution Mixture model Gibbs sampling Empirical Bayes method Bayesian inference Statistics Probability and statistics Bayesian statistics
57	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
58	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
59	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
60	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

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