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Conditional entropy
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11	2006 Paper 8 Question 16 Information Theory and Coding (a) Suppose we know the conditional entropy H(X\|Y ) for two slightly correlated discrete random variables X and Y . We wish to guess the value of X, from knowledge Add to Reading List Source URL: www.cl.cam.ac.uk Language: English - Date: 2014-06-09 10:18:14 Applied mathematics Fourier analysis Information theory Digital signal processing Sinc function Integral transforms Fourier transform Rectangular function Entropy Mathematical analysis Signal processing Mathematics
12	Performance analysis of OFDM modulation on indoor broadband PLC channels Add to Reading List Source URL: www.casmodeling.com Language: English Mathematics Mutual information Conditional mutual information Normal distribution Joint entropy Entropy Conditional entropy Markov chain Function Information theory Statistics Information
13	Performance analysis of OFDM modulation on indoor broadband PLC channels Add to Reading List Source URL: www.casmodeling.com Language: English Probability and statistics Mutual information Entropy Conditional entropy Regression analysis Granger causality Correlation and dependence Information theory Statistics Information
14	FROM FLAT DIRECT MODELS TO SEGMENTAL CRF MODELS Geoffrey Zweig and Patrick Nguyen Microsoft Corporation One Microsoft Way, Redmond, WAABSTRACT This paper summarizes recent work at Microsoft on the development of n Add to Reading List Source URL: research.microsoft.com Language: English - Date: 2010-01-06 19:40:40 Computational linguistics Conditional random field Maximum-entropy Markov model Speech recognition N-gram Language model Dynamic programming Part-of-speech tagging Information extraction Markov models Science Probability
15	A Segmental CRF Approach to Large Vocabulary Continuous Speech Recognition Geoffrey Zweig and Patrick Nguyen Microsoft Research, Redmond, WA {gzweig,panguyen}@microsoft.com Add to Reading List Source URL: research.microsoft.com Language: English - Date: 2009-09-05 12:53:28 Computational linguistics Statistical natural language processing Graphical models Theoretical computer science Maximum-entropy Markov model Speech recognition N-gram Conditional random field Hidden Markov model Markov models Probability Statistics
16	Supplemental Information 1. Appendix 1: Different definitions of cooperativity The MWC model features several interesting features in its most general form: i) indirect regulation and ii) cooperativity. There are severa Add to Reading List Source URL: www.rpgroup.caltech.edu Language: English - Date: 2013-12-19 21:13:26 Probability and statistics Mutual information Cooperative binding Entropy Kullback–Leibler divergence Conditional entropy Normal distribution Channel capacity Conditional probability Information theory Statistics Information
17	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
18	Estimating the Secrecy-Rate of Physical Unclonable Functions with the Context-Tree Weighting Method Tanya Ignatenko Geert-Jan Schrijen Add to Reading List Source URL: members.home.nl Language: English - Date: 2008-12-09 00:54:26 Theoretical computer science Mutual information Entropy Conditional entropy Joint entropy Conditioning Joint quantum entropy Information theory Information Statistics
19	Conditional Structure versus Conditional Estimation in NLP Models Dan Klein and Christopher D. Manning Computer Science Department Stanford University Stanford, CA[removed] {klein, manning}@cs.stanford.edu Add to Reading List Source URL: www.cs.berkeley.edu Language: English - Date: 2004-08-12 21:03:23 Linguistics Statistical natural language processing Computational linguistics Bayesian statistics Machine learning Maximum-entropy Markov model Hidden Markov model Part-of-speech tagging Word-sense disambiguation Statistics Markov models Science
20	CS 195-5: Machine Learning Problem Set 5 Douglas Lanman [removed] 26 November 2006 Add to Reading List Source URL: mesh.brown.edu Language: English - Date: 2006-11-28 13:11:01 Gaussian function Kernel density estimation Mutual information Normal distribution Entropy Correlation and dependence Conditional entropy Information theory Statistics Probability and statistics

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