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Mixture model
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271	➠ ➡ HIERARCHICAL CORRELATION COMPENSATION FOR HIDDEN MARKOV MODELS Hui Lin, Ye Tian, Jian-Lai Zhou, Hui Jiang** Dept. of Electronic Engineering, Tsinghua University, Beijing, China Add to Reading List Source URL: research.microsoft.com Language: English* - Date: 2009-08-10 10:41:28 Data analysis Algebra of random variables Summary statistics Covariance matrix Covariance Matrix Mixture model Linear discriminant analysis Hidden Markov model Statistics Covariance and correlation Multivariate statistics
272	LATENT COINCIDENCE ANALYSIS: A HIDDEN VARIABLE MODEL FOR DISTANCE METRIC LEARNING Matthew Der and Lawrence K. Saul, University of California, San Diego 1 INTRODUCTION Add to Reading List Source URL: cseweb.ucsd.edu Language: English - Date: 2012-12-11 16:44:37 Statistical models K-nearest neighbor algorithm Mixture model Estimation theory Expectation–maximization algorithm Statistics Machine learning Artificial intelligence
273	JOURNAL OF PAMI, VOL. ?, NO. ?, JANUARY 20?? 1 Modeling Natural Images Using Gated MRFs Marc’Aurelio Ranzato, Volodymyr Mnih, Joshua M. Susskind, Geoffrey E. Hinton Add to Reading List Source URL: www.cs.toronto.edu Language: English - Date: 2013-01-16 10:45:22 Psychometrics Multivariate statistics Machine learning Generative model Latent variable Principal component analysis Mixture model Normal distribution Multivariate normal distribution Statistics Statistical models Data analysis
274	Journal of Artificial Intelligence Research203 Submitted 11/12; publishedA Survey on Latent Tree Models and Applications Rapha¨ Add to Reading List Source URL: jair.org Language: English - Date: 2013-05-31 00:53:01 Latent variable Expectation–maximization algorithm Latent class model Bayesian network Graphical model Mixture model Marginal likelihood Statistics Statistical models Bayesian statistics
275	How reliable is my reliability model? Add to Reading List Source URL: www.mssanz.org.au Language: English - Date: 2013-01-16 21:21:38 Survival analysis Bayesian inference Model selection Statistical models Weibull distribution Deviance information criterion Mixture model Bayesian information criterion Reliability engineering Statistics Probability and statistics Bayesian statistics
276	PDF Document Add to Reading List Source URL: papers.nips.cc Language: English - Date: 2014-11-26 14:29:24 Machine learning Estimation theory Statistical theory Expectation–maximization algorithm Bayesian network Gibbs sampling Perceptron Kullback–Leibler divergence Mixture model Statistics Statistical models Neural networks
277	This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Cross-lingual Subspace Gaussian Mixture Models for Low-reso Add to Reading List Source URL: www.cstr.ed.ac.uk Language: English - Date: 2013-10-07 08:11:17 Markov models Regression analysis Automatic identification and data capture Speech recognition Hidden Markov model Mixture model Linear regression Maximum likelihood Conjugate prior Statistics Computational linguistics Estimation theory
278	Discussion Article Discussion Andreas BUJA Gelman’s article is a thought-provoking mix of opinions and creative methodology. I agree with Gelman that the disjunction of models and exploratory data analysis (EDA) Add to Reading List Source URL: stat.wharton.upenn.edu Language: English - Date: 2007-10-12 12:46:12 Resampling Confidence interval Non-parametric statistics Parameter Maximum a posteriori estimation Mixture model Empirical Bayes method Statistics Statistical inference Bootstrapping
279	Latent Class Models in Longitudinal Research Jeroen K. Vermunt Department of Methodology and Statistics, Tilburg University Bac Tran U.S. Census Bureau Jay Magidson Add to Reading List Source URL: statisticalinnovations.com Language: English - Date: 2008-01-22 12:06:02 Markov processes Categorical data Econometrics Latent class model Latent variable Expectation–maximization algorithm Hidden Markov model Markov chain Mixture model Statistics Statistical models Markov models
280	Understanding volatility dynamics in the EU-ETS market Maria Eugenia Sanin, Maria Mansanet-Bataller and Francesco Violante CREATES Research PaperDepartment of Economics and Business Add to Reading List Source URL: econ.au.dk Language: English - Date: 2015-01-15 03:10:00 Probability and statistics Technical analysis Carbon finance Emissions trading European Union Emission Trading Scheme Autoregressive conditional heteroskedasticity Volatility Mixture model Normal distribution Statistics Mathematical finance Climate change policy

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