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Information Theory and Statistical Learning
Information Theory and Statistical Learning
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Information Theory and Statistical Learning

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$293.00
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Description

"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
Release date NZ
November 4th, 2010
Audience
  • Professional & Vocational
Contributors
  • Edited by Frank Emmert-Streib
  • Edited by Matthias Dehmer
Edition
Softcover reprint of hardcover 1st ed. 2009
Illustrations
X, 439 p.
Pages
439
Dimensions
156x234x23
ISBN-13
9781441946508
Product ID
9974327

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