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Mixture distribution
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#	Item
1	Gaussian sampling by local perturbations George Papandreou Department of Statistics University of California, Los Angeles Add to Reading List Source URL: www.stat.ucla.edu Language: English - Date: 2010-10-31 18:18:15 Statistics Statistical models Stochastic processes Linear filters Bayesian statistics Estimation theory Gibbs sampling Normal distribution Kalman filter Mixture model Bayesian network Gaussian process
2	Scalable Training of Mixture Models via Coresets Dan Feldman MIT Matthew Faulkner Add to Reading List Source URL: eew.caltech.edu Language: English - Date: 2012-05-15 11:47:37 Statistics Probability Maximum likelihood estimation Probability distributions Bayesian statistics Expectationmaximization algorithm Mixture model Normal distribution K-means clustering Likelihood function Data stream clustering Gamma distribution
3	Maximum Likelihood Estimation of Dirichlet Distribution Parameters Jonathan Huang Abstract. Dirichlet distributions are commonly used as priors over proportional data. In this paper, I will introduce this distribution, d Add to Reading List Source URL: jonathan-huang.org Language: English - Date: 2014-09-08 21:47:30 Statistics Mathematical analysis Probability Probability distributions Gamma distribution Dirichlet distribution Exponential family Beta distribution Mixture model Multinomial distribution Likelihood function Maximum likelihood estimation
4	A Latent Dirichlet Allocation Model for Entity Resolution Indrajit Bhattacharya Lise Getoor University of Maryland Add to Reading List Source URL: drona.csa.iisc.ernet.in Language: English - Date: 2005-12-21 17:12:02 Probability Statistics Sampling Survey methodology Mixture model Gibbs sampling Record linkage Latent Dirichlet allocation Probability distribution Prior probability Causality
5	Correlated Community Estimation Models Over a Set of Names Suresh Veluru∗ , Yogachandran Rahulamathavan∗ , Suresh Manandhar† , and Muttukrishnan Rajarajan∗ ∗ Information Security Group, School of Engineering a Add to Reading List Source URL: www.uncertaintyofidentity.com Language: English - Date: 2014-11-25 09:34:28 Statistics Probability Probability distributions Statistical natural language processing Latent Dirichlet allocation Statistical models Mixture model Topic model Dirichlet distribution Multinomial distribution Gibbs sampling Perplexity
6	A Bayesian Approach to Learning 3D Representations of Dynamic Environments Ralf K¨astner, Nikolas Engelhard, Rudolph Triebel, and Roland Siegwart Abstract We propose a novel probabilistic approach to learning spatial re Add to Reading List Source URL: europa.informatik.uni-freiburg.de Language: English - Date: 2010-12-20 07:34:33 Statistics Statistical theory Estimation theory Bayesian statistics Statistical models Signal processing Cluster analysis Mixture model Maximum likelihood estimation Normal distribution K-means clustering Likelihood function
7	A Latent Variable Model for Geographic Lexical Variation Jacob Eisenstein Brendan O’Connor Noah A. Smith Eric P. Xing School of Computer Science Carnegie Mellon University Add to Reading List Source URL: homes.cs.washington.edu Language: English - Date: 2015-07-30 17:50:53 Statistics Probability Statistical natural language processing Probability distributions Estimation theory Regression analysis Dynamic topic model Latent Dirichlet allocation Variational Bayesian methods Mixture model Topic model Normal distribution
8	INTERSPEECHICSLP A Novel Framework of Text-independent Speaker Veriﬁcation based on Utterance Transform and Iterative Cohort Modeling Ming Liu, Huazhong Ning, Thomas S. Huang Add to Reading List Source URL: www.ifp.illinois.edu Language: English - Date: 2007-01-02 21:18:26 Statistics Probability Normal distribution Mixture model Maximum likelihood estimation
9	Variational Bayesian Learning of Cooperative Vector Quantizer Model - The Theory Add to Reading List Source URL: people.cs.pitt.edu Language: English - Date: 2003-05-06 15:46:12 Statistics Statistical models Bayesian network Latent variable Variational Bayesian methods Independent component analysis Expectationmaximization algorithm Generative model Principal component analysis Bayesian inference Normal distribution Mixture model
10	A Latent Dirichlet Model for Unsupervised Entity Resolution Indrajit Bhattacharya Lise Getoor Department of Computer Science University of Maryland, College Park, MDAbstract Add to Reading List Source URL: drona.csa.iisc.ernet.in Language: English - Date: 2006-02-01 15:14:20 Probability Statistics Probability distributions Stochastic processes Latent Dirichlet allocation Statistical natural language processing Mixture model Prior probability Dirichlet distribution Gibbs sampling Sampling Dirichlet process