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

Hardcover

ISBN 10: 3036543325 ISBN 13: 9783036543321

Verlag: MDPI AG, 2022

Inhaltsangabe

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 Rényi 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.

Details zur Ausgabe

• Verlag: MDPI AG
• Erscheinungsdatum: 2022
• Sprache: Englisch
• ISBN 10: 3036543325
• ISBN 13: 9783036543321
• Einband: Gebundene Ausgabe
• Anzahl der Seiten: 256
• Herausgeber: Sason Igal
• Kontakt zum Hersteller: preigu GmbH & Co. KG; mail@preigu.de; ; Lengericher Landstr. 19; Osnabrück; Niedersachsen; 49078; Deutschland