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Conjugate prior
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#	Item
171	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
172	Variational Bayesian Image Modelling Li Cheng Department of Computing Science, University of Alberta, Canada Feng Jiao School of Computer Science, University of Waterloo, Canada Add to Reading List Source URL: www.machinelearning.org Language: English - Date: 2008-12-01 11:15:09 Model selection Estimation theory Statistical theory Expectation–maximization algorithm Gamma distribution Variational Bayesian methods Bayesian information criterion Conjugate prior Kullback–Leibler divergence Statistics Bayesian statistics Bayesian inference
173	International Journal of Computer Vision 75(2), 267–282, 2007 c 2007 Springer Science + Business Media, LLC. Manufactured in the United States. DOI: [removed]s11263[removed]POP: Patchwork of Parts Models for Objec Add to Reading List Source URL: www.stat.uchicago.edu Language: English - Date: 2014-04-22 17:05:50 Bayesian statistics Statistical models Measurement Expectation–maximization algorithm Missing data Constellation model Conjugate prior Likelihood function Dimensional analysis Statistics Estimation theory Probability and statistics
174	Bayesian Inference for Transductive Learning of Kernel Matrix Using the Tanner-Wong Data Augmentation Algorithm Zhihua Zhang [removed] Dit-Yan Yeung Add to Reading List Source URL: www.machinelearning.org Language: English - Date: 2008-12-01 11:20:03 Expectation–maximization algorithm Missing data Matrix Conjugate prior Support vector machine Markov chain Statistics Statistical classification Estimation theory
175	Tempering for Bayesian C&RT Nicos Angelopoulos [removed] James Cussens [removed] Add to Reading List Source URL: www.machinelearning.org Language: English - Date: 2008-12-01 11:14:12 Markov chain Bayesian network Posterior probability Conjugate prior Metropolis–Hastings algorithm Maximum likelihood Bayes estimator Naive Bayes classifier Bayesian inference in phylogeny Statistics Bayesian statistics Bayesian inference
176	Bayesian Hierarchical Clustering Katherine A. Heller Zoubin Ghahramani Gatsby Computational Neuroscience Unit, UCL, London, WC1N 3AR, UK Add to Reading List Source URL: www.machinelearning.org Language: English - Date: 2008-12-01 11:14:20 Bayesian statistics Bioinformatics Data mining Single-linkage clustering Hierarchical clustering Mixture model Conjugate prior Dirichlet process Hidden Markov model Statistics Machine learning Cluster analysis
177	PDF Document Add to Reading List Source URL: www.clevelandfed.org Language: English - Date: 2011-10-27 14:41:25 Econometrics Statistical forecasting Bayesian VAR Vector autoregression Conjugate prior Forecasting Bayesian inference Macroeconomic model Economic model Statistics Bayesian statistics Time series analysis
178	Bayesian Analysis[removed], Number 4, pp. 817–846 A Case for Robust Bayesian Priors with Applications to Clinical Trials Add to Reading List Source URL: ba.stat.cmu.edu Language: English - Date: 2009-11-26 03:35:42 Conjugate prior Normal distribution Robust Bayes analysis Prior probability Exponential family Bayesian inference Parameter Maximum likelihood Poisson distribution Statistics Bayesian statistics Probability and statistics
179	Apprenticeship Learning for Model Parameters of Partially Observable Environments Takaki Makino [removed] Institute of Industrial Science, the University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo[removed]Ja Add to Reading List Source URL: icml.cc Language: English - Date: 2012-06-07 13:20:26 Dynamic programming Stochastic control Estimation theory Partially observable Markov decision process Markov decision process Apprenticeship learning Reinforcement learning Conjugate prior Automated planning and scheduling Statistics Markov processes Markov models
180	Monte Carlo Bayesian Reinforcement Learning Yi Wang WANGY @ COMP. NUS . EDU . SG Kok Sung Won KOKSUNG @ COMP. NUS . EDU . SG Add to Reading List Source URL: icml.cc Language: English - Date: 2012-06-07 13:20:16 Stochastic control Markov models Partially observable Markov decision process Bayesian statistics Reinforcement learning Markov decision process Conjugate prior Markov chain Q-learning Statistics Markov processes Dynamic programming

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