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Bayesian statistics
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#	Item
411	Bayesian regularization of non-homogeneous dynamic Bayesian networks by globally coupling interaction parameters Marco Grzegorczyk Department of Statistics TU Dortmund University Add to Reading List Source URL: jmlr.csail.mit.edu Language: English - Date: 2012-04-26 08:56:33
412	Randomized Algorithms for Fast Bayesian Hierarchical Clustering Katherine A. Heller and Zoubin Ghahramani Gatsby Computational Neuroscience Unit University College London, London, WC1N 3AR, UK {heller,zoubin}@gatsby.ucl. Add to Reading List Source URL: www.gatsby.ucl.ac.uk Language: English - Date: 2005-10-18 12:07:50 Data mining Geostatistics Hierarchical clustering Mixture model Unsupervised learning Randomized algorithm Data stream clustering Consensus clustering Statistics Machine learning Cluster analysis
413	Exchangeable Inconsistent Priors for Bayesian Posterior Inference Max Welling Ian Porteous Add to Reading List Source URL: www.ics.uci.edu Language: English - Date: 2012-02-01 15:33:24 Dirichlet process Poisson distribution Principle of maximum entropy Prior probability Normal distribution Mixture model Gibbs sampling Empirical Bayes method Bayesian inference Statistics Probability and statistics Bayesian statistics
414	Using Bayesian Aldrich-McKelvey Scaling to Study Citizens’ Ideological Preferences and Perceptions Christopher Hare Department of Political Science, University of Georgia 104 Baldwin Hall Athens, GA 30602 Add to Reading List Source URL: www.voteview.com Language: English - Date: 2014-07-02 11:51:42 Bayesian statistics Science Marketing Prior probability Scale Bayesian inference Survey methodology Statistics Psychometrics Market research
415	Catching Up Faster in Bayesian Model Selection and Model Averaging (T61) Peter Gru¨ nwald Tim van Erven 1. Introduction & Summary Add to Reading List Source URL: www.timvanerven.nl Language: English - Date: 2012-06-05 11:28:52 Statistical inference Bayesian inference Markov models Markov chain Akaike information criterion Bayes factor Estimation theory Graphical model Expectation–maximization algorithm Statistics Bayesian statistics Model selection
416	Incremental Learning of Nonparametric Bayesian Mixture Models Ryan Gomes∗ Max Welling† ∗ Add to Reading List Source URL: www.ics.uci.edu Language: English - Date: 2008-04-09 01:39:03 Cluster analysis Data analysis Estimation theory Expectation–maximization algorithm Dirichlet process Variational Bayesian methods Mixture model Principal component analysis Kernel principal component analysis Statistics Multivariate statistics Machine learning
417	Subgroup Discovery Meets Bayesian Networks—An Exceptional Model Mining Approach Add to Reading List Source URL: www.cs.uu.nl Language: English - Date: 2011-02-16 08:30:43 Graphical models Networks Bayesian network Group theory Machine learning Subgroup Statistics Bayesian statistics Statistical models
418	Predicting AGI: What can we say when we know so little? Fallenstein, Benja Mennen, Alex Add to Reading List Source URL: intelligence.org Language: English - Date: 2013-12-02 15:06:01 Actuarial science Exponentials Bayesian statistics Probability theory Pareto distribution Socioeconomics Strong AI Normal distribution Stable distribution Statistics Probability and statistics Probability
419	Efficient Gradient-Based Inference through Transformations between Bayes Nets and Neural Nets Diederik P. Kingma Max Welling Machine Learning Group, University of Amsterdam Add to Reading List Source URL: www.ics.uci.edu Language: English - Date: 2014-05-14 15:18:52 Statistical models Statistical theory Statistical inference Expectation–maximization algorithm Bayesian network Gibbs sampling Normal distribution Maximum likelihood Latent variable Statistics Bayesian statistics Estimation theory
420	An Alternative Prior Process for Nonparametric Bayesian Clustering Hanna M. Wallach Department of Computer Science University of Massachusetts Amherst Add to Reading List Source URL: www.gatsby.ucl.ac.uk Language: English - Date: 2010-03-15 18:50:30 Pitman–Yor process Chinese restaurant process Dirichlet distribution Concentration parameter Mixture model Bayesian inference Prior probability Statistics Stochastic processes Dirichlet process

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