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Expectation–maximization algorithm
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501	ICM 2002 · Vol. III · 1–3 Pattern Theory: the Mathematics of Perception David Mumford∗ Add to Reading List Source URL: www.csee.wvu.edu Language: English - Date: 2008-08-18 10:37:07 Probability theory Markov processes Statistical dependence Markov chain Pattern theory Hidden Markov model Markov property Expectation–maximization algorithm Stochastic process Statistics Markov models Statistical models
502	TECHNICAL WHITE PAPER \| TLD Suggestion System 1 TLD Suggestion System A probabilistic model for the TLD suggestion Add to Reading List Source URL: pres.gandi.net Language: English - Date: 2014-12-22 07:28:00 Identifiers Top-level domains Exponentials Expectation–maximization algorithm Mixture model Maximum likelihood Domain name Normal distribution Dirichlet process Statistics Domain name system Estimation theory
503	Combining Spatial and Telemetric Features for Learning Animal Movement Models Berk Kapicioglu (Princeton University), Robert E. Schapire (Princeton University), Martin Wikelski (Max Planck Institute for Ornithology), Tam Add to Reading List Source URL: www.berkkapicioglu.com Language: English - Date: 2013-11-30 21:06:22 Missing data Random walk Statistics Estimation theory Expectation–maximization algorithm
504	EM Decipherment for Large Vocabularies Malte Nuhn and Hermann Ney Human Language Technology and Pattern Recognition Computer Science Department, RWTH Aachen University, Aachen, Germany @cs.rwth-aachen.de Add to Reading List Source URL: www-i6.informatik.rwth-aachen.de Language: English Expectation–maximization algorithm Statistics Substitution cipher Cipher
505	A note on Bayesian logistic regression for spatial exponential family Gibbs point processes Tuomas A. Rajala Department of Mathematical Sciences Chalmers University of Technology and University of Gothenburg S[removed]Goth Add to Reading List Source URL: tuomas.sokkelo.net Language: English - Date: 2014-09-23 12:33:42 Bayesian statistics Estimation theory Statistical theory Expectation–maximization algorithm Exponential family Generalized linear model Parametric model Connection Confidence interval Statistics Statistical models Regression analysis
506	An exciting opportunity exists for motivated and enthusiastic Postdoctoral Research Fellows to contribute to the research undertaken at the ARC Centre of Excellence for Mathematical and Statistical Frontiers. The Postdoc Add to Reading List Source URL: qut.nga.net.au Language: English - Date: 2014-09-30 02:18:36 Statistical forecasting Estimation theory Bayesian inference Statistical theory Markov chain Monte Carlo Machine learning Approximate Bayesian computation Quasi-likelihood Expectation–maximization algorithm Statistics Bayesian statistics Statistical inference
507	EM Decipherment for Large Vocabularies Malte Nuhn and Hermann Ney Human Language Technology and Pattern Recognition Computer Science Department, RWTH Aachen University, Aachen, Germany @cs.rwth-aachen.de Add to Reading List Source URL: www-i6.informatik.rwth-aachen.de Language: English Expectation–maximization algorithm Statistics Substitution cipher Cipher
508	NISS Secure Regression for Vertically Partitioned, Partially Overlapping Data Jerome P. Reiter, Christine N. Kohnen, Alan F. Karr Xiaodong Lin, and Ashish P. Sanil Add to Reading List Source URL: www.niss.org Language: English - Date: 2004-10-21 14:14:40 Estimation theory Data analysis Expectation–maximization algorithm Missing data Linear regression Multivariate normal distribution Variance Normal distribution Statistics Econometrics Regression analysis
509	Natural Belief-Critic: a reinforcement algorithm for parameter estimation in statistical spoken dialogue systems F. Jurˇc´ıcˇ ek, B. Thomson, S. Keizer, F. Mairesse, M. Gaˇsi´c, K. Yu, and S. Young Engineering Depa Add to Reading List Source URL: mi.eng.cam.ac.uk Language: English - Date: 2010-11-01 08:12:32 Dynamic programming Stochastic control Markov models Expectation–maximization algorithm Partially observable Markov decision process Maximum likelihood Reinforcement learning Markov chain Normal distribution Statistics Markov processes Estimation theory
510	PARAMETER LEARNING FOR POMDP SPOKEN DIALOGUE MODELS B. Thomson, F. Jurˇc´ıcˇ ek, M. Gaˇsi´c, S. Keizer, F. Mairesse, K. Yu, S. Young Cambridge University Engineering Department ABSTRACT The partially observable Mar Add to Reading List Source URL: mi.eng.cam.ac.uk Language: English - Date: 2010-11-09 15:42:38 Estimation theory Expectation–maximization algorithm Maximum likelihood Partially observable Markov decision process Parameter Kullback–Leibler divergence Normal distribution Bayesian network Dialogue Statistics Statistical theory Bayesian statistics

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