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Entropy maximization
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#	Item
21	On the Design and Quantification of Privacy Preserving Data Mining Algorithms Dakshi Agrawal Charu C. Aggarwal Add to Reading List Source URL: www.charuaggarwal.net Language: English - Date: 2006-11-17 15:35:44 Statistical theory Expectation–maximization algorithm Missing data Normal distribution Mutual information Logarithm Entropy Maximum likelihood Variational Bayesian methods Statistics Estimation theory Information theory
22	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
23	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
24	MAXIMUM ENTROPY RELAXATION FOR GRAPHICAL MODEL SELECTION GIVEN INCONSISTENT STATISTICS Venkat Chandrasekaran, Jason K. Johnson, Alan S. Willsky Laboratory for Information and Decision Systems Department of Electrical Eng Add to Reading List Source URL: users.cms.caltech.edu Language: English - Date: 2012-02-01 13:45:54 Bayesian statistics Information theory Statistical models Exponential family Expectation–maximization algorithm Maximum likelihood Principle of maximum entropy Fisher information Entropy Statistics Estimation theory Statistical theory
25	Finding Progression Stages in Time-evolving Event Sequences † Jaewon Yang† Julian McAuley† Jure Leskovec† Paea LePendu‡ Nigam Shah‡ Computer Science, Stanford University, {jayang, jmcauley, jure}@cs.stanford. Add to Reading List Source URL: cseweb.ucsd.edu Language: English - Date: 2014-07-10 21:46:58 Regression analysis Categorical data Maximum likelihood Expectation–maximization algorithm Logistic regression Entropy Sequence Statistics Statistical theory Estimation theory
26	16 Density Estimation We’ve learned more and more about how to describe and fit functions, but the decision to fit a function can itself be unduly restrictive. Instead of assuming a noise model for the data (such as G Add to Reading List Source URL: fab.cba.mit.edu Language: English - Date: 2014-04-14 17:27:29 Estimation theory Bayesian statistics Expectation–maximization algorithm Missing data Normal distribution Kernel density estimation Entropy Maximum likelihood Principle of maximum entropy Statistics Statistical theory Non-parametric statistics
27	This article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal non-commercial research and education use, including for instruction at the authors institution and shar Add to Reading List Source URL: www.cs.columbia.edu Language: English - Date: 2014-11-25 10:45:20 Markov chain Expectation–maximization algorithm Kullback–Leibler divergence Probability distribution Probability Information bottleneck method Maximum-entropy Markov model Statistics Markov models Hidden Markov model
28	236 IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. 28, NO. 2, Add to Reading List Source URL: vis-www.cs.umass.edu Language: English - Date: 2008-01-02 15:36:33 Thresholding Expectation–maximization algorithm Pixel Entropy One-shot learning Image processing Statistics Computer graphics
29	Finding Progression Stages in Time-evolving Event Sequences Jaewon Yang†∗ Julian McAuley† Jure Leskovec† Paea LePendu‡ Nigam Shah‡ † Computer Science, Stanford University, {jayang, jmcauley, jure}@cs.stanfo Add to Reading List Source URL: cs.stanford.edu Language: English - Date: 2014-03-02 10:25:32 Regression analysis Categorical data Maximum likelihood Expectation–maximization algorithm Logistic regression Entropy Sequence Statistics Statistical theory Estimation theory
30	Statistical Properties of Probabilistic Context-Free Grammars Z h i y i Chi* Add to Reading List Source URL: acl.ldc.upenn.edu Language: English - Date: 2002-06-11 09:28:00 Stochastic context-free grammar Kullback–Leibler divergence Entropy Principle of maximum entropy Expectation–maximization algorithm Information theory Distribution Expected value Information bottleneck method Statistics Probability and statistics Statistical theory

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