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Expectation–maximization algorithm
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521	The Annals of Statistics 2012, Vol. 40, No. 4, 1935–1967 DOI: [removed]AOS949 © Institute of Mathematical Statistics, 2012 LATENT VARIABLE GRAPHICAL MODEL SELECTION VIA Add to Reading List Source URL: users.cms.caltech.edu Language: English - Date: 2012-11-07 21:35:11 Multivariate statistics Data analysis Summary statistics Expectation–maximization algorithm Matrix Latent variable model Multivariate normal distribution Covariance matrix Principal component analysis Statistics Covariance and correlation Statistical models
522	Privacy Aware Learning 1 John C. Duchi1 Michael I. Jordan1,2 Add to Reading List Source URL: www.cs.berkeley.edu Language: English - Date: 2012-11-25 05:12:43 Information theory Decision theory Econometrics Loss function Mutual information Dimensional analysis Divergence Maximum likelihood Expectation–maximization algorithm Statistics Statistical theory Estimation theory
523	Approximate inference for the loss-calibrated Bayesian Simon Lacoste-Julien University of Cambridge 1 Add to Reading List Source URL: www.di.ens.fr Language: English - Date: 2011-12-02 09:14:29 Bayesian statistics Econometrics Bayesian inference Expectation–maximization algorithm Loss function Kullback–Leibler divergence Bayes estimator Marginal likelihood Maximum likelihood Statistics Estimation theory Statistical theory
524	MAXIMUM ENTROPY RELAXATION FOR GRAPHICAL MODEL SELECTION GIVEN INCONSISTENT STATISTICS Venkat Chandrasekaran, Jason K. Johnson, Alan S. Willsky Laboratory for Information and Decision Systems Department of Electrical Eng Add to Reading List Source URL: users.cms.caltech.edu Language: English - Date: 2012-02-01 13:45:54 Bayesian statistics Information theory Statistical models Exponential family Expectation–maximization algorithm Maximum likelihood Principle of maximum entropy Fisher information Entropy Statistics Estimation theory Statistical theory
525	P1: FIC OJ002-04 April 12, [removed]:23 Add to Reading List Source URL: mqscores.berkeley.edu Language: English - Date: 2014-07-14 18:26:26 Markov models Bayesian statistics Time series analysis Expectation–maximization algorithm Kalman filter Prior probability Normal distribution Regression analysis Autoregressive conditional heteroskedasticity Statistics Econometrics Estimation theory
526	Cross-lingual Projected Expectation Regularization for Weakly Supervised Learning Mengqiu Wang and Christopher D. Manning Computer Science Department Stanford University Stanford, CA[removed]USA Add to Reading List Source URL: nlp.stanford.edu Language: English - Date: 2014-07-16 02:05:44 Computational linguistics Econometrics Bitext word alignment Machine translation Estimation theory Conditional random field Semi-supervised learning Named-entity recognition Expectation–maximization algorithm Statistics Machine learning Science
527	Finding Progression Stages in Time-evolving Event Sequences † Jaewon Yang† Julian McAuley† Jure Leskovec† Paea LePendu‡ Nigam Shah‡ Computer Science, Stanford University, {jayang, jmcauley, jure}@cs.stanford. Add to Reading List Source URL: cseweb.ucsd.edu Language: English - Date: 2014-07-10 21:46:58 Regression analysis Categorical data Maximum likelihood Expectation–maximization algorithm Logistic regression Entropy Sequence Statistics Statistical theory Estimation theory
528	Learning Latent Personas of Film Characters David Bamman Brendan O’Connor Noah A. Smith School of Computer Science Carnegie Mellon University Pittsburgh, PA 15213, USA {dbamman,brenocon,nasmith}@cs.cmu.edu Add to Reading List Source URL: www.aclweb.org Language: English - Date: 2013-07-25 09:24:47 Role-playing video games Human–computer interaction Persona Technical communication Usability Topic model Latent Dirichlet allocation Expectation–maximization algorithm Concentration parameter Statistics Statistical natural language processing Machine learning
529	Unified Expectation Maximization Rajhans Samdani University of Illinois [removed] Ming-Wei Chang Add to Reading List Source URL: web.engr.illinois.edu Language: English - Date: 2012-05-18 17:57:19 Expectation–maximization algorithm Missing data Semi-supervised learning Kullback–Leibler divergence Statistics Machine learning Estimation theory
530	A weakly informative default prior distribution for logistic and other regression models Add to Reading List Source URL: www.stat.columbia.edu Language: English - Date: 2009-01-13 21:34:46 Linear regression Generalized linear model Separation Least squares Poisson regression Normal distribution Expectation–maximization algorithm Predictive analytics Multinomial logit Statistics Regression analysis Logistic regression

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