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Mixture model
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#	Item
651	5. Mixtures and Products of Experts University of Cambridge Engineering Part IIB Module 4F10: Statistical Pattern Processing Add to Reading List Source URL: mi.eng.cam.ac.uk Language: English - Date: 2013-11-13 04:10:48 Maximum likelihood Likelihood function Multivariate normal distribution Mixture model Normal distribution Statistics Estimation theory Expectation–maximization algorithm
652	Space-time zero-inflated count models of Harbor seals Add to Reading List Source URL: www.alaskafisheries.noaa.gov Language: English - Date: 2009-08-20 12:43:58 Statistical models Actuarial science Spatial data analysis Poisson distribution Generalized linear model Overdispersion Negative binomial distribution Mixture model Spatial analysis Statistics Regression analysis Categorical data
653	Model-Based Approaches to Handling Uncertainty M.J.F. Gales Abstract A powerful approach for handling uncertainty in observations is to modify the statistical model of the data to appropriately reflect this uncertainty. Add to Reading List Source URL: mi.eng.cam.ac.uk Language: English - Date: 2010-09-03 04:10:35 Statistical inference Markov models Statistical models Multivariate normal distribution Speech recognition Hidden Markov model Additive white Gaussian noise Mixture model Linear regression Statistics Estimation theory Regression analysis
654	Learning Stochastic Feedforward Neural Networks Yichuan Tang Department of Computer Science University of Toronto Toronto, Ontario, Canada. Add to Reading List Source URL: www.cs.toronto.edu Language: English - Date: 2013-11-19 21:06:13 Machine learning Estimation theory Statistical theory Expectation–maximization algorithm Bayesian network Gibbs sampling Perceptron Kullback–Leibler divergence Mixture model Statistics Statistical models Neural networks
655	Truncation-free Stochastic Variational Inference for Bayesian Nonparametric Models Chong Wang⇤ Machine Learning Department Carnegie Mellon University [removed] Add to Reading List Source URL: www.cs.princeton.edu Language: English - Date: 2012-11-10 21:14:58 Dirichlet process Latent Dirichlet allocation Mixture model Bayesian inference Importance sampling Inference Conjugate prior Hierarchical Bayes model Dirichlet distribution Statistics Bayesian statistics Variational Bayesian methods
656	TT+GT at TRECVID 2010 Workshop Nakamasa Inoue Toshiya Wada Yusuke Kamishima Koichi Shinoda Department of Computer Science, Add to Reading List Source URL: www-nlpir.nist.gov Language: English - Date: 2011-03-04 14:18:53 Statistical models Econometrics Support vector machine Mixture model Normal distribution Generalized method of moments Parameter Statistics Probability and statistics Statistical classification
657	TokyoTech+Canon at TRECVID 2011 Nakamasa Inoue Yusuke Kamishima Toshiya Wada Koichi Shinoda Department of Computer Science, Add to Reading List Source URL: www-nlpir.nist.gov Language: English - Date: 2012-03-05 09:28:37 Machine learning Histogram of oriented gradients Scale-invariant feature transform Mixture model Generalized method of moments Support vector machine Cross-validation Statistics Computer vision Artificial intelligence
658	Latent Semantic Indexing for Video Content Modeling and Analysis Fabrice Souvannavong, Bernard Merialdo and Benoˆıt Huet D´epartement Communications Multim´edias Institut Eur´ecom 2229, route des crˆetes Add to Reading List Source URL: www-nlpir.nist.gov Language: English - Date: 2004-03-02 12:00:19 Information retrieval Natural language processing Science Latent semantic indexing Latent semantic analysis Statistical classification Mixture model K-nearest neighbor algorithm Semantic analysis Information science Machine learning Artificial intelligence
659	Understanding the Limiting Factors of Topic Modeling via Posterior Contraction Analysis Jian Tang1 TANGJIAN @ NET. PKU . EDU . CN Zhaoshi Meng2 Add to Reading List Source URL: jmlr.org Language: English - Date: 2014-02-16 19:30:21 Latent Dirichlet allocation Topic model Cluster analysis Machine learning Natural language processing Mixture model Dirichlet distribution Statistical inference Statistical hypothesis testing Statistics Statistical natural language processing Psychometrics
660	Spatial distance dependent Chinese restaurant processes for image segmentation Soumya Ghosh1 , Andrei B. Ungureanu2 , Erik B. Sudderth1 , and David M. Blei3 1 Department of Computer Science, Brown University, {sghosh,su Add to Reading List Source URL: www.cs.princeton.edu Language: English - Date: 2011-11-29 11:07:08 Cluster analysis Image processing Segmentation Market segmentation Dirichlet process K-means clustering Mixture model Chinese restaurant process Spectral clustering Statistics Stochastic processes Machine learning

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