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Principle of maximum entropy
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141	? Objective Bayesianism and the Maximum Entropy Principle ? Jürgen Landes and Jon Williamson Draft of September 3, 2013 Add to Reading List Source URL: www.kent.ac.uk Language: English - Date: 2013-09-03 09:46:50 Information theory Mathematics Philosophy of thermal and statistical physics Thermodynamic entropy Principle of maximum entropy Entropy Connection Kullback–Leibler divergence Probability space Statistics Statistical theory Probability and statistics
142	Learning Tractable Word Alignment Models with Complex Constraints João V. Graça∗ 2 L F INESC-ID Add to Reading List Source URL: homes.cs.washington.edu Language: English - Date: 2013-04-28 17:51:54 Bayesian statistics Information theory Kullback–Leibler divergence Thermodynamics Expectation–maximization algorithm Maximum likelihood Principle of maximum entropy Entropy Divergence Statistics Statistical theory Estimation theory
143	Chapter 13 Epistemic Complexity from an Objective Bayesian Perspective Jon Williamson Add to Reading List Source URL: www.kent.ac.uk Language: English - Date: 2010-05-12 11:34:56 Statistical theory Philosophy of science Statistical inference Probability theory Bayesian probability Bayesian inference Bayesian network Principle of maximum entropy Dempster–Shafer theory Statistics Bayesian statistics Probability and statistics
144	Information and Entropy A NIMBioS Investigative Workshop April 8-10, 2015 NIMBioS at the Univ. of Tennessee, Knoxville Information theory and entropy methods are becoming powerful tools in biology, from the level of indi Add to Reading List Source URL: math.ucr.edu Language: English - Date: 2014-07-04 04:08:38 Statistical theory State functions Cybernetics Thermodynamic entropy Biostatistics National Institute for Mathematical and Biological Synthesis Entropy Information theory Principle of maximum entropy Science Statistics Applied mathematics
145	How biased are maximum entropy models? Jakob H. Macke Gatsby Computational Neuroscience Unit University College London, UK [removed] Add to Reading List Source URL: www.gatsby.ucl.ac.uk Language: English - Date: 2011-11-16 10:58:04 Information theory Randomness Estimation theory Statistical inference Entropy Principle of maximum entropy Kullback–Leibler divergence Maximum likelihood Mutual information Statistics Probability and statistics Statistical theory
146	Comput Manag Sci DOI[removed]s10287[removed]ORIGINAL PAPER Calibrating probability distributions with convexconcave-convex functions: application to CDO pricing Add to Reading List Source URL: www.ise.ufl.edu Language: English - Date: 2013-07-30 14:13:11 Probability Principle of maximum entropy Probability distribution Convex optimization Entropy Log-normal distribution Probability density function Maximum entropy probability distribution Statistics Probability and statistics Statistical theory
147	SUPPORT VECTOR MACHINE AND MAXIMUM LIKELIHOOD APPROACHES TO F-MEASURE OPTIMIZATION Trevor Rose Supervisor: A/ Prof. Spiridon Penev Add to Reading List Source URL: www.ontotext.com Language: English - Date: 2014-08-19 16:38:16 Linear classifier Support vector machine Binary classification Principle of maximum entropy Automatic summarization Margin classifier Random subspace method Statistics Statistical classification Machine learning
148	Journal of Machine Learning Research[removed]Submitted 4/00; Published[removed]Likelihood and F-measure maximization under uncertainty Georgi Dimitroff Add to Reading List Source URL: www.ontotext.com Language: English - Date: 2014-08-19 16:38:16 Kullback–Leibler divergence Thermodynamics Weight Principle of maximum entropy Mean Exponential distribution Maximum spacing estimation Statistics Statistical theory Probability and statistics
149	DEPARTMENT OF ECONOMICS UNIVERSITY OF CYPRUS THE MM, ME, ML, EL, EF AND GMM APPROACHES TO ESTIMATION: A SYNTHESIS Add to Reading List Source URL: www.ucy.ac.cy Language: English - Date: 2013-07-03 07:17:13 Estimation theory Information theory Normal distribution Uniform distribution Principle of maximum entropy Entropy Maximum likelihood Generalized method of moments Akaike information criterion Statistics Probability and statistics Statistical theory
150	Cold-start Active Learning with Robust Ordinal Matrix Factorization Neil Houlsby1 Jos´e Miguel Hern´andez-Lobato1 Zoubin Ghahramani University of Cambridge, Department of Engineering, Cambridge CB2 1PZ, UK Add to Reading List Source URL: mlg.eng.cam.ac.uk Language: English - Date: 2014-07-12 13:27:52 Statistical models Regression analysis Markov models Mixture model Kullback–Leibler divergence Variational Bayesian methods Bayesian inference Naive Bayes classifier Principle of maximum entropy Statistics Bayesian statistics Statistical theory

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