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Gibbs sampling
Results: 303

#	Item
221	Bayesian Time Series Models and Scalable Inference by Matthew James Johnson B.S. Electrical Engineering and Computer Sciences, UC Berkeley, 2008 S.M. Electrical Engineering and Computer Science, MIT, 2010 Add to Reading List Source URL: ssg.mit.edu Language: English - Date: 2014-06-19 14:35:03 Markov models Statistical theory Bioinformatics Hidden Markov model Bayesian inference Hidden semi-Markov model Gibbs sampling Graphical model Non-parametric statistics Statistics Bayesian statistics Statistical inference
222	Curve Sampling and Geometric Conditional Simulation by Ayres C. Fan B.S., Electrical Engineering University of Minnesota, 2000 S.M., Electrical Engineering and Computer Science Add to Reading List Source URL: ssg.mit.edu Language: English - Date: 2012-02-01 13:34:49 Applied mathematics Monte Carlo methods Markov chain Monte Carlo Theoretical computer science Computational statistics Markov chain Metropolis–Hastings algorithm Gibbs sampling Segmentation Statistics Probability and statistics Markov models
223	Subject Index original example, 30 Bayesian data analysis, three steps of, 3 Bayesian filtering and smoothing, 516 Behrens–Fisher problem, 80 belief functions, 98 Add to Reading List Source URL: www.stat.columbia.edu Language: English - Date: 2013-09-18 03:45:49 Empirical Bayes method Conjugate prior Linear regression Mixture model Deviance information criterion Calibration Gibbs sampling Bootstrapping Nonparametric regression Statistics Regression analysis Generalized linear model
224	Relaxed Marginal Inference and its Application to Dependency Parsing Sebastian Riedel David A. Smith Department of Computer Science University of Massachusetts, Amherst {riedel,dasmith}@cs.umass.edu Add to Reading List Source URL: www.ccs.neu.edu Language: English - Date: 2010-04-02 15:00:32 Mathematics Belief propagation Factor graph Inference Gibbs sampling Tree decomposition Forward–backward algorithm Bayesian network Markov random field Graph theory Graphical models Statistics
225	Bayesian Haplotype Inference via the Dirichlet Process Eric Xing† [removed] Roded Sharan† [removed] Add to Reading List Source URL: www.machinelearning.org Language: English - Date: 2008-12-01 11:20:48 Population genetics Genetic genealogy Haplotype Dirichlet process Mixture model Expectation–maximization algorithm Gibbs sampling Dirichlet distribution Hardy–Weinberg principle Statistics Genetics Classical genetics
226	1533 Integrated stock mixture analysis for continous and categorical data, with application to genetic– otolith combinations Stephen J. Smith and Steven E. Campana Add to Reading List Source URL: www.bio.gc.ca Language: English - Date: 2014-01-08 08:23:59 Fish anatomy Auditory system Otolith Paleontology Hardy–Weinberg principle Prior probability Confidence interval Bayes estimator Gibbs sampling Statistics Bayesian statistics Statistical inference
227	Package ‘iFad’ July 2, 2014 Type Package Title An integrative factor analysis model for drug-pathway association inference Version 3.0 Date[removed] Add to Reading List Source URL: cran.r-project.org Language: English - Date: 2014-07-02 12:09:50 Markov chain Monte Carlo Matrix Probability distribution Factor analysis Fisher information Statistics Multivariate statistics Gibbs sampling
228	Laplace Maximum Margin Markov Networks Jun Zhu†∗ [removed] Eric P. Xing† [removed] Bo Zhang∗ Add to Reading List Source URL: www.machinelearning.org Language: English - Date: 2008-05-21 03:17:20 Machine learning Graphical models Conditional random field Theoretical computer science Kullback–Leibler divergence Pattern recognition Gibbs sampling Support vector machine Principle of maximum entropy Statistics Statistical theory Bayesian statistics
229	Naive Bayes Models for Probability Estimation Daniel Lowd LOWD @ CS . WASHINGTON . EDU Pedro Domingos PEDROD @ CS . WASHINGTON . EDU Add to Reading List Source URL: www.machinelearning.org Language: English - Date: 2008-12-01 11:15:48 Probability theory Statistical models Networks Bayesian network Gibbs sampling Naive Bayes classifier Markov random field Expectation–maximization algorithm Belief propagation Statistics Bayesian statistics Graphical models
230	Bayesian Inference for Finite-State Transducers∗ David Chiang1 Jonathan Graehl1 Kevin Knight1 Add to Reading List Source URL: aclweb.org Language: English - Date: 2010-06-14 21:27:14 Statistical inference Statistical theory Machine learning Expectation–maximization algorithm Gibbs sampling Hidden Markov model Bayesian inference Variational Bayesian methods Pattern recognition Statistics Bayesian statistics Estimation theory

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