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

• Andere auteurs: Sason, Igal (Redacteur)
• Formaat: Elektronisch Hoofdstuk
• Taal: Engels
• Gepubliceerd in: Basel MDPI - Multidisciplinary Digital Publishing Institute 2022
• Onderwerpen: Research & information: general; Mathematics & science; 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; n/a
• Online toegang: DOAB: download the publication; DOAB: description of the publication

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...