Information Theory and Statistical Learning Paperback - 2010
by Frank Emmert-Streib (Editor); Matthias Dehmer (Editor)
From the rear 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
Details
- Title Information Theory and Statistical Learning
- Author Frank Emmert-Streib (Editor); Matthias Dehmer (Editor)
- Binding Paperback
- Edition Softcover reprin
- Pages 439
- Volumes 1
- Language ENG
- Publisher Springer
- Date 2010-11-04
- ISBN 9781441946508 / 1441946500
- Weight 1.38 lbs (0.63 kg)
- Dimensions 9.21 x 6.14 x 0.91 in (23.39 x 15.60 x 2.31 cm)
- Dewey Decimal Code 004.015
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Information Theory and Statistical Learning
by Frank Emmert-Streib
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- ISBN 10 / ISBN 13
- 9781441946508 / 1441946500
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