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Bayesian inference
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#	Item
661	MACQUARIE UNIVERSITY STATISTICS DEPARTMENT SEMINAR Speaker: Dr Bob Carpenter, Department of Statistics, Columbia University Date: Tuesday 10 March 2015, Time 2pm Venue: E4A523 Title: Add to Reading List Source URL: stat.mq.edu.au Language: English - Date: 2015-03-02 23:53:39 Bayesian statistics Statistical theory Bayesian inference Statistical forecasting Inference Statistics Logic Statistical inference
662	Integrating confidence intervals, likelihoods and confidence distributions Tor Schweder∗, Nils L. Hjort University of Oslo, Norway Abstract Add to Reading List Source URL: www.statistics.gov.hk Language: English - Date: 2013-08-22 04:39:19 Statistical theory Bayesian statistics Confidence interval Measurement Likelihood function Normal distribution Fiducial inference Statistics Statistical inference Estimation theory
663	Empirical Minimum Bayes Risk Prediction: How to extract an extra few% performance from vision models with just three more parameters Vittal Premachandran* National University of Singapore Add to Reading List Source URL: filebox.ece.vt.edu Language: English - Date: 2014-04-22 19:35:34 Estimation theory Bayesian inference Statistical theory Empirical risk minimization Supervised learning Loss function Bayes estimator Regression analysis Image Statistics Econometrics Machine learning
664	Learning Community-based Preferences via Dirichlet Process Mixtures of Gaussian Processes Ehsan Abbasnejad Scott Sanner ANU & NICTA NICTA & ANU Add to Reading List Source URL: users.cecs.anu.edu.au Language: English - Date: 2015-03-17 00:39:18 Markov chain Normal distribution Dirichlet process Bayesian inference Marginal likelihood Conjugate prior Statistics Bayesian statistics Mixture model
665	Applied Nonparametric Bayes Michael I. Jordan Department of Electrical Engineering and Computer Science Department of Statistics University of California, Berkeley http://www.cs.berkeley.edu/∼jordan Add to Reading List Source URL: www.siam.org Language: English - Date: 2009-06-18 10:03:04 Statistical inference Philosophy of science Statistical models Bayesian inference Dirichlet process Frequentist inference Exchangeable random variables Parametric model Hierarchical Bayes model Statistics Bayesian statistics Statistical theory
666	Theory and Dynamics of Perceptual Bistability Paul R. Schrater∗ Departments of Psychology and Computer Sci. & Eng. University of Minnesota Minneapolis, MN 55455 Add to Reading List Source URL: outobox.cs.umn.edu Language: English - Date: 2006-11-22 23:08:30 Bayesian inference Estimation theory Statistical inference Probability distribution Maximum a posteriori estimation Statistics Statistical theory Bayesian statistics
667	Cooperative Multi-Agent Inference over Grid Structured Markov Random Fields Ryan K. Williams and Gaurav S. Sukhatme Abstract— In this work we investigate cooperative inference in multi-agent systems where uncertainty i Add to Reading List Source URL: robotics.usc.edu Language: English - Date: 2013-06-01 19:27:52 Probability theory Networks Statistical models Probability and statistics Mathematics Belief propagation Markov random field Bayesian network Probabilistic logic Graphical models Statistics Bayesian statistics
668	George Box: The legacy of an ‘Accidental Statistician’ Bovas Abraham University of Waterloo, Waterloo, Canada George E.P. Box was one of the greatest statistical minds of the 20th century, and Add to Reading List Source URL: www.statistics.gov.hk Language: English - Date: 2013-08-22 04:39:21 Industrial engineering Quality Statistical methods George E. P. Box Bayesian inference Power transform Response surface methodology Statistics Statistical theory Design of experiments
669	CS-TR-4956 UMIACS-TRLAMP-TR-153 June 2010 Add to Reading List Source URL: www.cs.umd.edu Language: English - Date: 2011-01-03 11:18:10 Monte Carlo methods Markov models Markov chain Monte Carlo Estimation theory Markov chain Expectation–maximization algorithm Gibbs sampling Importance sampling Bayesian inference Statistics Probability and statistics Bayesian statistics
670	Modeling Dependable Systems using Hybrid Bayesian Networks Martin Neil†‡, Manesh Tailor‡, David Marquez†, Norman Fenton†‡ and Peter Hearty† † Department of Computer Science, Queen Mary, University of Lon Add to Reading List Source URL: www.agenarisk.com Language: English - Date: 2010-02-23 15:24:03 Bayesian inference Markov chain Probability distribution Graphical model Conjugate prior Statistics Bayesian statistics Bayesian network

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