Items related to Information Theory: From Coding to Learning

Information Theory: From Coding to Learning - Hardcover

Polyanskiy, Yury; Wu, Yihong

 
9781108832908: Information Theory: From Coding to Learning
Hardcover
ISBN 10: 1108832903 ISBN 13: 9781108832908
Publisher: Cambridge University Press, 2024

Synopsis

An enthusiastic introduction to the fundamentals of information theory, from classical Shannon theory to modern statistical learning.

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About the Authors

Yury Polyanskiy is a Professor of Electrical Engineering and Computer Science at the Massachusetts Institute of Technology, with a focus on information theory, statistical machine learning, error-correcting codes, wireless communication, and fault tolerance. He is the recipient of the 2020 IEEE Information Theory Society James Massey Award for outstanding achievement in research and teaching in Information Theory.

Yihong Wu is a Professor of Statistics and Data Science at Yale University, focusing on the theoretical and algorithmic aspects of high-dimensional statistics, information theory, and optimization. He is the recipient of the 2018 Sloan Research Fellowship in Mathematics.

"About this title" may belong to another edition of this title.

Publisher
Cambridge University Press
Publication date
2024
Language
English
ISBN 10 
1108832903
ISBN 13 
9781108832908
Binding
Hardcover
Number of pages
550