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Entropy maximization
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11	Semi-Supervised Conditional Random Fields for Improved Sequence Segmentation and Labeling Feng Jiao University of Waterloo Abstract We present a new semi-supervised training Add to Reading List Source URL: webdocs.cs.ualberta.ca Language: English - Date: 2006-12-28 15:24:48 Statistical theory Estimation theory Conditional random field Theoretical computer science Supervised learning Kullback–Leibler divergence Semi-supervised learning Expectation–maximization algorithm Conditional entropy Statistics Machine learning Information theory
12	A Continuum from Mixtures to Products: Aggregation under Bias Amos J. Storkey Zhanxing Zhu Jinli Hu School of Informatics,University of Edinburgh Add to Reading List Source URL: bigml.cs.tsinghua.edu.cn Language: English - Date: 2014-06-22 05:40:20 Probability and statistics Kullback–Leibler divergence Rényi entropy Expectation–maximization algorithm Entropy Perplexity Principle of maximum entropy Statistics Information theory Statistical theory
13	doi:[removed]j.cviu[removed] Add to Reading List Source URL: profs.sci.univr.it Language: English - Date: 2011-10-29 17:50:38 Hidden Markov model Segmentation Cluster analysis Markov chain Region growing Expectation–maximization algorithm Entropy Layered hidden Markov model Statistics Markov models Image processing
14	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
15	STAT 538 Lecture 8 Maximum Entropy Models c Marina Meil˘a Add to Reading List Source URL: www.stat.washington.edu Language: English - Date: 2015-02-17 20:52:05 Bayesian statistics Kullback–Leibler divergence Thermodynamics Normal distribution Principle of maximum entropy Convex optimization Expectation–maximization algorithm Entropy Maximum entropy probability distribution Statistics Probability and statistics Statistical theory
16	MultiTarget Estimation in Noise and Clutter M.Malyutov Department of Mathematics Northeastern University Boston MA 02115, [removed], Add to Reading List Source URL: www.ams.sunysb.edu Language: English Kalman filter Normal distribution Logarithm Maximum likelihood Cross-entropy method M-estimator Statistics Estimation theory Expectation–maximization algorithm
17	Proc. Indian Acad. Sci. (Math. Sci.) Vol. 119, No. 4, September 2009, pp. 531–539. © Printed in India Entropy maximization K B ATHREYA Department of Mathematics and Statistics, Iowa State University, USA Add to Reading List Source URL: eprints.iisc.ernet.in Language: English - Date: 2010-09-19 01:52:36 Multivariate normal distribution Measure theory Symbol Spectral theory of ordinary differential equations Mathematical analysis Statistics Normal distribution
18	Proceedings of ACL ’93, pp[removed]DISTRIBUTIONAL CLUSTERING OF ENGLISH WORDS Fernando Pereira AT&T Bell Laboratories Add to Reading List Source URL: www.cs.cornell.edu Language: English - Date: 2002-08-29 18:38:04 Information theory Hierarchical clustering Kullback–Leibler divergence Entropy Maximum likelihood Cross entropy Expectation–maximization algorithm Cluster analysis Determining the number of clusters in a data set Statistics Statistical theory Principle of maximum entropy
19	Proc. Indian Acad. Sci. (Math. Sci.) Vol. 119, No. 4, September 2009, pp. 531–539. © Printed in India Entropy maximization K B ATHREYA Department of Mathematics and Statistics, Iowa State University, USA Add to Reading List Source URL: www.ias.ac.in Language: English - Date: 2012-12-05 01:46:41 Multivariate normal distribution Measure theory Symbol Spectral theory of ordinary differential equations Mathematical analysis Statistics Normal distribution
20	Combining Mixture Components for Clustering Add to Reading List Source URL: www.stat.washington.edu Language: English - Date: 2011-05-24 20:39:20 Mixture model Hierarchical clustering Computer cluster Entropy Expectation–maximization algorithm Determining the number of clusters in a data set Statistics Cluster analysis Machine learning

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