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Bayesian
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#	Item
271	Bayesian Pseudorandom Algorithms Ike Antkare International Institute of Technology United Slates of Earth Add to Reading List Source URL: membres-lig.imag.fr Language: English - Date: 2014-01-09 04:24:29 Actor model Concurrent computing
272	Learning stick-figure models using nonparametric Bayesian priors over trees Edward W. Meeds, David A. Ross, Richard S. Zemel, and Sam T. Roweis Department of Computer Science University of Toronto {ewm, dross, zemel, row Add to Reading List Source URL: www.cs.toronto.edu Language: English - Date: 2008-08-08 22:07:31 Statistics Probability Statistical theory Probability distributions Statistical models Bayesian statistics Stochastic processes Graphical models Bayesian network Gibbs sampling Dirichlet process Mixture model
273	That was fast! Speeding up NN search of high dimensional distributions. Emanuele Coviello University of California, San Diego, 9500 Gilman Dr, La Jolla, CA 92093 Add to Reading List Source URL: eceweb.ucsd.edu Language: English - Date: 2015-07-31 19:02:39 Statistics Geometry Statistical distance Information Statistical theory Information theory Bregman divergence Search algorithms KullbackLeibler divergence Variational Bayesian methods Expectationmaximization algorithm Divergence
274	A Short Introduction to Probabilistic Soft Logic Angelika Kimmig1,2 , Stephen H. Bach1 , Matthias Broecheler3 , Bert Huang1 , Lise Getoor1 1 University of Maryland, 2 KU Leuven, 3 Aurelius LLC Add to Reading List Source URL: stephenbach.net Language: English - Date: 2013-06-10 18:15:10 Logic Philosophy Abstraction Bayesian statistics Markov networks Reasoning Model theory Semantics Probabilistic soft logic Markov logic network Probabilistic logic Statistical relational learning
275	Clever Bookies and Coherent Beliefs David Christensen The Philosophical Review, Vol. 100, No. 2. (Apr., 1991), ppStable URL: http://links.jstor.org/sici?sici=%%29100%3A2%3C229%3ACBACB%3E2.0.CO Add to Reading List Source URL: dl.dropboxusercontent.com Language: English Philosophy Epistemology Probability Wagering Probability interpretations Bayesian probability Philosophy of mathematics Philosophy of science Dutch book Coherence Rationality Henry E. Kyburg Jr.
276	Mean Field Variational Approximations in Continuous-Time Markov Processes A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science Add to Reading List Source URL: www.cs.huji.ac.il Language: English - Date: 2015-08-10 08:23:20 Bayesian statistics Statistics Graphical models Probability Markov models Bayesian network Probability distribution Markov chain Expectation propagation Approximate inference Likelihood function Hidden Markov model
277	S TATC MSC 35425: T OPICS IN S TATISTICAL M ACHINE L EARNING Syllabus, Spring 2016 Topics in Statistical Machine Learning is a second course in machine learning, with students assumed to have previous exposure t Add to Reading List Source URL: galton.uchicago.edu Language: English - Date: 2016-04-13 06:56:12 Statistics Machine learning Artificial intelligence Learning Statistical models Language modeling Word embedding Pattern recognition Bayesian inference Mixture model Artificial neural network Higher-order singular value decomposition
278	Collective Activity Detection using Hinge-loss Markov Random Fields Ben London, Sameh Khamis, Stephen H. Bach, Bert Huang, Lise Getoor, Larry Davis University of Maryland College Park, MD 20742 {blondon,sameh,bach,bert,g Add to Reading List Source URL: psl.umiacs.umd.edu Language: English - Date: 2013-06-14 19:26:52 Artificial intelligence Probability Statistics Bayesian statistics Markov networks Graphical models Markov random field Probability theory Image segmentation Probabilistic soft logic Activity recognition Support vector machine
279	Mission Energy Prediction for Unmanned Ground Vehicles Using Realtime Measurements and Prior Knowledge Add to Reading List Source URL: robotics.umich.edu Language: English - Date: 2016-08-04 12:43:38 Statistics Statistical theory Estimation theory Bayesian statistics Statistical inference Unmanned ground vehicle Prediction Regression analysis Prognostics Confidence interval Normal distribution Recursive least squares filter
280	Scalable Training of Mixture Models via Coresets Dan Feldman MIT Matthew Faulkner Add to Reading List Source URL: eew.caltech.edu Language: English - Date: 2012-05-15 11:47:37 Statistics Probability Maximum likelihood estimation Probability distributions Bayesian statistics Expectationmaximization algorithm Mixture model Normal distribution K-means clustering Likelihood function Data stream clustering Gamma distribution

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