Divergence Measures : Mathematical Foundations and Applications in Information-Theoretic and Statistical Problems

Divergence Measures : Mathematical Foundations and Applications in Information-Theoretic and Statistical Problems

Data science, information theory, probability theory, statistical learning and other related disciplines greatly benefit from non-negative measures of dissimilarity between pairs of probability measures. These are known as divergence measures, and exploring their mathematical foundations and diverse...

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Sason, Igal
Year of Publication:2022
Language:English
Physical Description:1 electronic resource (256 p.)
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spelling Sason, Igal edt
Divergence Measures Mathematical Foundations and Applications in Information-Theoretic and Statistical Problems
Divergence Measures
Basel MDPI - Multidisciplinary Digital Publishing Institute 2022
1 electronic resource (256 p.)
text txt rdacontent
computer c rdamedia
online resource cr rdacarrier
Data science, information theory, probability theory, statistical learning and other related disciplines greatly benefit from non-negative measures of dissimilarity between pairs of probability measures. These are known as divergence measures, and exploring their mathematical foundations and diverse applications is of significant interest. The present Special Issue, entitled “Divergence Measures: Mathematical Foundations and Applications in Information-Theoretic and Statistical Problems”, includes eight original contributions, and it is focused on the study of the mathematical properties and applications of classical and generalized divergence measures from an information-theoretic perspective. It mainly deals with two key generalizations of the relative entropy: namely, the R_ényi divergence and the important class of f -divergences. It is our hope that the readers will find interest in this Special Issue, which will stimulate further research in the study of the mathematical foundations and applications of divergence measures.
English
Research & information: general bicssc
Mathematics & science bicssc
Bregman divergence
f-divergence
Jensen-Bregman divergence
Jensen diversity
Jensen-Shannon divergence
capacitory discrimination
Jensen-Shannon centroid
mixture family
information geometry
difference of convex (DC) programming
conditional Rényi divergence
horse betting
Kelly gambling
Rényi divergence
Rényi mutual information
relative entropy
chi-squared divergence
f-divergences
method of types
large deviations
strong data-processing inequalities
information contraction
maximal correlation
Markov chains
information inequalities
mutual information
Rényi entropy
Carlson-Levin inequality
information measures
hypothesis testing
total variation
skew-divergence
convexity
Pinsker's inequality
Bayes risk
statistical divergences
minimum divergence estimator
maximum likelihood
bootstrap
conditional limit theorem
Bahadur efficiency
α-mutual information
Augustin-Csiszár mutual information
data transmission
error exponents
dimensionality reduction
discriminant analysis
statistical inference
3-0365-4332-5
3-0365-4331-7
Sason, Igal oth
language English
format eBook
author2 Sason, Igal
author_facet Sason, Igal
author2_variant i s is
author2_role Sonstige
title Divergence Measures Mathematical Foundations and Applications in Information-Theoretic and Statistical Problems
spellingShingle Divergence Measures Mathematical Foundations and Applications in Information-Theoretic and Statistical Problems
title_sub Mathematical Foundations and Applications in Information-Theoretic and Statistical Problems
title_full Divergence Measures Mathematical Foundations and Applications in Information-Theoretic and Statistical Problems
title_fullStr Divergence Measures Mathematical Foundations and Applications in Information-Theoretic and Statistical Problems
title_full_unstemmed Divergence Measures Mathematical Foundations and Applications in Information-Theoretic and Statistical Problems
title_auth Divergence Measures Mathematical Foundations and Applications in Information-Theoretic and Statistical Problems
title_alt Divergence Measures
title_new Divergence Measures
title_sort divergence measures mathematical foundations and applications in information-theoretic and statistical problems
publisher MDPI - Multidisciplinary Digital Publishing Institute
publishDate 2022
physical 1 electronic resource (256 p.)
isbn 3-0365-4332-5
3-0365-4331-7
illustrated Not Illustrated
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