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Expectation–maximization algorithm
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171	Multiple Imputation of Missing Values in Economic Surveys: Comparison of Competing Algorithms Masayoshi Takahashi* National Statistics Center, Tokyo, Japan Takayuki Ito National Statistics Center, Add to Reading List Source URL: www.statistics.gov.hk Language: English - Date: 2013-08-22 04:38:58 Markov models Computational statistics Imputation Monte Carlo methods Markov chain Monte Carlo Expectation–maximization algorithm Markov chain Bootstrapping SPSS Statistics Data analysis Missing data
172	A Note on Expectation Maximization Algorithm Dawei Yin Department of Computer Science & Engineering, Lehigh University Bethlehem, PAUSA 29 Mar. 2013 Add to Reading List Source URL: wume.cse.lehigh.edu Language: English - Date: 2013-03-30 12:23:30 Missing data Statistical theory Complex analysis Maximum likelihood Variational Bayesian methods Statistics Estimation theory Expectation–maximization algorithm
173	Journal of Machine Learning Research–1816 Submitted 4/05; Revised 10/05; PublishedProbabilistic Non-linear Principal Component Analysis with Gaussian Process Latent Variable Models Add to Reading List Source URL: jmlr.csail.mit.edu Language: English - Date: 2005-11-20 10:42:17 Principal component analysis Expectation–maximization algorithm Gaussian process Generative topographic map Covariance matrix Mixture model Conjugate prior Factor analysis Covariance function Statistics Multivariate statistics Kernel principal component analysis
174	EM for Perceptual Coding and Reinforcement Learning Tasks Yuri Ivanov Bruce Blumberg Alex Pentland Add to Reading List Source URL: characters.media.mit.edu Language: English - Date: 2003-06-30 17:30:06 Estimation theory Expectation–maximization algorithm Missing data Reinforcement learning Mixture model Q-learning Algorithm Pattern recognition Statistics Machine learning Computational statistics
175	Microsoft Word - OWC CCR 2010.doc Add to Reading List Source URL: www.mauirealestatesearch.com Language: English Normal distribution Expectation–maximization algorithm Multivariate normal distribution Principal component analysis Wishart distribution Linear regression Symbol Conjugate prior Statistics Estimation theory Multivariate statistics
176	Sparse Bayesian Multi-Task Learning C´edric Archambeau, Shengbo Guo, Onno Zoeter Xerox Research Centre Europe {Cedric.Archambeau, Shengbo.Guo, Onno.Zoeter}@xrce.xerox.com Add to Reading List Source URL: users.cecs.anu.edu.au Language: English - Date: 2011-10-28 18:26:19 Normal distribution Expectation–maximization algorithm Multivariate normal distribution Principal component analysis Wishart distribution Linear regression Symbol Conjugate prior Statistics Estimation theory Multivariate statistics
177	Expectation Maximization for Weakly Labeled Data Yuri Ivanov MIT Media Laboratory, 20 Ames St., E15-390, Cambridge, MA 02139, USA Add to Reading List Source URL: characters.media.mit.edu Language: English - Date: 2003-06-30 17:21:48 Maximum likelihood Kullback–Leibler divergence M-estimator Likelihood function Reinforcement learning Divergence Multi-armed bandit Marginal likelihood Extremum estimator Statistics Estimation theory Expectation–maximization algorithm
178	A Meta-Theory of Boundary Detection Benchmarks Xiaodi Hou Computation and Neural Systems, Caltech Add to Reading List Source URL: www.its.caltech.edu Language: English - Date: 2013-02-24 22:01:40 Expectation–maximization algorithm Missing data Segmentation Statistics Image processing Estimation theory
179	Copyright  2000 by the Genetics Society of America Inference of Population Structure Using Multilocus Genotype Data Jonathan K. Pritchard, Matthew Stephens and Peter Donnelly Department of Statistics, University of O Add to Reading List Source URL: pritchardlab.stanford.edu Language: English - Date: 2013-11-05 20:00:40 Genetic genealogy Classical genetics Statistical genetics Machine learning Hardy–Weinberg principle Cluster analysis Allele frequency Markov chain Expectation–maximization algorithm Statistics Genetics Population genetics
180	Bayesian Estimation of Sparse Smooth Speckle Shape Models for Motion Tracking in Medical Ultrasound MOTIVATION In this work, we aim at adapting the speckle tracking echocardiography (STE) technique for measuring strain i Add to Reading List Source URL: homepages.ulb.ac.be Language: English - Date: 2014-11-17 05:12:09 Interference Cardiac imaging Speckle tracking echocardiography Speckle pattern Expectation–maximization algorithm Medical ultrasonography Frame Medicine Medical ultrasound Statistics

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