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Mixture theory
Results: 438

#	Item
251	Nonparametric Variational Inference Samuel J. Gershman [removed] Department of Psychology, Princeton University, Green Hall, Princeton, NJ[removed]USA Matthew D. Hoffman Add to Reading List Source URL: www.cs.princeton.edu Language: English - Date: 2012-06-05 15:28:29 Estimation theory Statistical models Statistical theory Variational Bayesian methods Probability theory Conjugate prior Mixture model Marginal likelihood Kullback–Leibler divergence Statistics Bayesian statistics Probability and statistics
252	INTERSPEECH[removed]Inﬁnite Support Vector Machines in Speech Recognition Jingzhou Yang, Rogier C. van Dalen and Mark Gales Department of Engineering, University of Cambridge Trumpington Street, Cambridge, CB2 1PZ, UK Add to Reading List Source URL: mi.eng.cam.ac.uk Language: English - Date: 2013-09-24 18:34:41 Stochastic processes Statistical classification Statistical theory Mixture model Parametric model Dirichlet process Hidden Markov model Generative model Support vector machine Statistics Statistical models Machine learning
253	The Discrete Infinite Logistic Normal Distribution for Mixed-Membership Modeling John Paisley, Chong Wang and David Blei Department of Computer Science, Princeton University {jpaisley,chongw,blei}@princeton.edu Add to Reading List Source URL: www.cs.princeton.edu Language: English - Date: 2011-05-12 14:11:18 Statistical inference Statistical theory Variational Bayesian methods Latent Dirichlet allocation Gamma distribution Dirichlet process Mixture model Normal distribution Gamma function Statistics Bayesian statistics Statistical natural language processing
254	Fast Speaker Diarization Using a High-Level Scripting Language Ekaterina Gonina #1 , Gerald Friedland ∗2 , Henry Cook #3 , Kurt Keutzer #4 # University of California, Berkeley Add to Reading List Source URL: www.eecs.berkeley.edu Language: English - Date: 2011-08-20 00:34:35 Graphics hardware Estimation theory Machine learning Video cards CUDA Generalized method of moments Mixture model Segmentation Expectation–maximization algorithm Statistics Computing GPGPU
255	Predicting Legislative Roll Calls from Text Sean M. Gerrish SGERRISH @ CS . PRINCETON . EDU David M. Blei BLEI @ CS . PRINCETON . EDU Add to Reading List Source URL: www.cs.princeton.edu Language: English - Date: 2011-05-12 14:11:19 Statistical natural language processing Natural language processing Bayesian statistics Statistical models Statistical theory Topic model Mixture model Latent Dirichlet allocation Information retrieval Statistics Science Probability and statistics
256	COMPARISON OF LARGE MARGIN TRAINING TO OTHER DISCRIMINATIVE METHODS FOR PHONETIC RECOGNITION BY HIDDEN MARKOV MODELS Fei Sha∗ Lawrence K. Saul† Add to Reading List Source URL: www-bcf.usc.edu Language: English - Date: 2011-08-01 12:49:00 Expectation–maximization algorithm Hidden Markov model Maximum likelihood Mixture model Likelihood function Generalized method of moments Statistics Estimation theory Speech recognition
257	Fast Allocation of Gaussian Process Experts Trung V. Nguyen ANU & NICTA VTNGUYEN @ NICTA . COM . AU Add to Reading List Source URL: jmlr.org Language: English - Date: 2014-02-16 19:30:21 Statistical theory Gaussian process Mixture model Kriging Errors and residuals in statistics Statistics Regression analysis Machine learning
258	Seriation in Paleontological Data Using Markov Chain Monte Carlo Methods Kai Puolama¨ki1, Mikael Fortelius2, Heikki Mannila3 1 Laboratory of Computer and Information Science, Helsinki University of Technology, Espoo, F Add to Reading List Source URL: www.helsinki.fi Language: English* - Date: 2010-03-17 09:49:13 Markov models Statistical inference Estimation theory Statistical theory Maximum parsimony Markov chain Mixture model Seriation Likelihood function Statistics Probability and statistics Bayesian statistics
259	Variational Inference for the Nested Chinese Restaurant Process Chong Wang Computer Science Department Princeton University Add to Reading List Source URL: www.cs.princeton.edu Language: English - Date: 2010-08-18 22:20:55 Variational Bayesian methods Statistical models Expectation–maximization algorithm Dirichlet process Gibbs sampling Mixture model Bayesian inference Exponential family Kullback–Leibler divergence Statistics Bayesian statistics Statistical theory
260	Clustering through Mixture Models General references: Lindsay B.G[removed]), Mixture models: theory, geometry and applications, NFSCBMS Regional Conference Series in Probability and Statistics. McLachlan G.J., Basford K.E. Add to Reading List Source URL: globin.cse.psu.edu Language: English - Date: 2002-02-21 11:52:34 K-means clustering Expectation–maximization algorithm Cluster analysis Principal component analysis Variance Multivariate normal distribution Statistics Data analysis Multivariate statistics

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