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Expectation–maximization algorithm
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#	Item
401	Training deformable part models with decorrelated features Ross Girshick and Jitendra Malik UC Berkeley {rbg, malik}@eecs.berkeley.edu Abstract Add to Reading List Source URL: www.cs.berkeley.edu Language: English - Date: 2013-10-14 17:32:54 Multivariate statistics Linear discriminant analysis Histogram of oriented gradients Support vector machine Expectation–maximization algorithm Filter Estimation theory Statistics Statistical classification Signal processing
402	Shared Logistic Normal Distributions for Soft Parameter Tying in Unsupervised Grammar Induction Shay B. Cohen and Noah A. Smith Language Technologies Institute School of Computer Science Carnegie Mellon University Add to Reading List Source URL: www.cs.cmu.edu Language: English - Date: 2009-03-31 16:28:07 Estimation theory Bayesian statistics Statistical theory Bioinformatics Expectation–maximization algorithm Variational Bayesian methods Gamma distribution Multinomial distribution Dirichlet distribution Statistics Probability and statistics Statistical natural language processing
403	Composite Statistical Inference for Semantic Segmentation Fuxin Li(1) , Joao Carreira(2) , Guy Lebanon(1) , Cristian Sminchisescu[removed]Georgia Institute of Technology. (2) ISR - University of Coimbra. (3) Lund Universi Add to Reading List Source URL: www.eecs.berkeley.edu Language: English - Date: 2014-06-04 23:25:14 Maximum likelihood Expectation–maximization algorithm Identifiability Score Likelihood function Parametric model M-estimator Mixture model Entailment Statistics Estimation theory Segmentation
404	Mixture models for describing some strange looking datasets Add to Reading List Source URL: www.rsc.org Language: English - Date: 2014-08-20 04:20:15 Statistical models Statistical theory Expectation–maximization algorithm Missing data Mixture model Maximum likelihood Least squares Normal distribution Mixture distribution Statistics Estimation theory Regression analysis
405	CS 294-2, Grouping and Recognition (Prof. Jitendra Malik) Aug 30, 1999 Lecture #3 (Maximum likelihood framework) DRAFT Notes by Joshua Levy Add to Reading List Source URL: www.eecs.berkeley.edu Language: English - Date: 2003-07-25 14:52:15 Normal distribution Expectation–maximization algorithm Estimator Likelihood function M-estimator Estimation of covariance matrices Statistics Estimation theory Maximum likelihood
406	CS 294-2, Grouping and Recognition (Prof. Jitendra Malik) Sept 1st, 1999 Lecture #4 (Expectation Maximization Algorithm) DRAFT Notes by Rene Vidal Mixture models with incomplete data Add to Reading List Source URL: www.eecs.berkeley.edu Language: English - Date: 2003-07-25 14:54:43 Statistical theory Expectation–maximization algorithm Missing data Normal distribution Mixture model Maximum likelihood Multivariate normal distribution Statistics Estimation theory Cluster analysis
407	An Empirical Comparison of Techniques for Handling Incomplete Data Using Decision Trees BHEKISIPHO TWALA Modelling and Digital Intelligence, CSIR, P O Box 395, Pretoria 0001, South Africa ________________________________ Add to Reading List Source URL: researchspace.csir.co.za Language: English - Date: 2011-01-28 14:41:17 Machine learning Decision trees Imputation Data mining Decision tree learning Data set Expectation–maximization algorithm Supervised learning Censoring Statistics Data analysis Missing data
408	Parallelized Variational EM for Latent Dirichlet Allocation: An Experimental Evaluation of Speed and Scalability Ramesh Nallapati, William Cohen and John Lafferty Machine Learning Department Carnegie Mellon University 50 Add to Reading List Source URL: www.cs.cmu.edu Language: English - Date: 2007-09-24 14:58:31 Missing data Latent Dirichlet allocation Linear discriminant analysis Statistics Estimation theory Expectation–maximization algorithm
409	Recognizing Activities in Multiple Contexts using Transfer Learning T.L.M. van Kasteren and G. Englebienne and B.J.A. Kr¨ose Intelligent Systems Lab Amsterdam (ISLA) Science Park, Kruislaan 403, 1098 SJ Amsterdam, The N Add to Reading List Source URL: www.aaai.org Language: English - Date: 2008-10-15 16:33:56 Markov models Estimation theory Statistical theory Expectation–maximization algorithm Activity recognition Hidden Markov model Maximum likelihood Semi-supervised learning Pattern recognition Statistics Machine learning Artificial intelligence
410	Probabilistic Classification and Clustering in Relational Data Ben Taskar Eran Segal Daphne Koller Add to Reading List Source URL: ai.stanford.edu Language: English - Date: 2005-10-03 21:16:26 Machine learning Graphical models Cluster analysis Relational model Expectation–maximization algorithm Relation Probabilistic relational model Bayesian network Data mining Statistics Probability and statistics Statistical models

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