Information Theory : From Coding to Learning

Language: English

Published by Cambridge University Pr. Jan 2025, 2025

1108832903 / 9781108832908

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Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH

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Neuware - This enthusiastic introduction to the fundamentals of information theory builds from classical Shannon theory through to modern applications in statistical learning, equipping students with a uniquely well-rounded and rigorous foundation for further study. Introduces core topics such as data compression, channel coding, and rate-distortion theory using a unique finite block-length approach. With over 210 end-of-part exercises and numerous examples, students are introduced to contemporary applications in statistics, machine learning and modern communication theory. This textbook presents information-theoretic methods with applications in statistical learning and computer science, such as f-divergences, PAC Bayes and variational principle, Kolmogorov's metric entropy, strong data processing inequalities, and entropic upper bounds for statistical estimation. Accompanied by a solutions manual for instructors, and additional standalone chapters on more specialized topics in information theory, this is the ideal introductory textbook for senior undergraduate and graduate students in electrical engineering, statistics, and computer science.

Seller Inventory # 9781108832908

Title
Information Theory : From Coding to Learning
Author
Yury Polyanskiy
Publisher
Cambridge University Pr. Jan 2025
Publication year
2025
Condition
Neu
Binding
Buch
Language
English
ISBN 10
1108832903
ISBN 13
9781108832908
Item weight
1,683 grams
Dimensions
260x183x44 mm

AHA-BUCH GmbH

Einbeck, Germany

5-star seller

AbeBooks seller since August 14, 2006

Shipping rates from Germany to U.S.A.

Item7 to 10 business days5 to 7 business days
First itemUS$ 49.09US$ 58.87
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