Information Theory and Statistical Learning
Language: English
Published by Springer, 2008
- Hardcover
- Used
Seller: Better World Books: West, Reno, NV, U.S.A.Better World Books: West
AbeBooks seller since March 14, 2016
Condition: Used - Fine
US$ 91.32
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Seller Inventory # 57884603-75
- Title
- Information Theory and Statistical Learning
- Publisher
- Springer
- Publication year
- 2008
- Condition
- Fine
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 0387848150
- ISBN 13
- 9780387848150
- Item weight
- 3.924 pounds
- Dimensions
- N/A
"Information Theory and Statistical Learning" presents theoretical and practical results about information theoretic methods used in the context of statistical learning.
The book will present a comprehensive overview of the large range of different methods that have been developed in a multitude of contexts. Each chapter is written by an expert in the field. The book is intended for an interdisciplinary readership working in machine learning, applied statistics, artificial intelligence, biostatistics, computational biology, bioinformatics, web mining or related disciplines.
Advance Praise for "Information Theory and Statistical Learning":
"A new epoch has arrived for information sciences to integrate various disciplines such as information theory, machine learning, statistical inference, data mining, model selection etc. I am enthusiastic about recommending the present book to researchers and students, because it summarizes most of these new emerging subjects and methods, which are otherwise scattered in many places." Shun-ichi Amari, RIKEN Brain Science Institute, Professor-Emeritus at the University of Tokyo
"Synopsis" may belong to another edition of this title.
From the Back Cover
Information Theory and Statistical Learning presents theoretical and practical results about information theoretic methods used in the context of statistical learning.
The book will present a comprehensive overview of the large range of different methods that have been developed in a multitude of contexts. Each chapter is written by an expert in the field. The book is intended for an interdisciplinary readership working in machine learning, applied statistics, artificial intelligence, biostatistics, computational biology, bioinformatics, web mining or related disciplines.
Advance Praise for Information Theory and Statistical Learning:
"A new epoch has arrived for information sciences to integrate various disciplines such as information theory, machine learning, statistical inference, data mining, model selection etc. I am enthusiastic about recommending the present book to researchers and students, because it summarizes most of these new emerging subjects and methods, which are otherwise scattered in many places."
-- Shun-ichi Amari, RIKEN Brain Science Institute, Professor-Emeritus at the University of Tokyo
"About the title" may belong to another edition of this title.
Better World Books: West
Reno, NV, U.S.A.
AbeBooks seller since March 14, 2016
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