Téléchargez le livre : Information Theory and Statistical Learning

Information Theory and Statistical Learning

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Éditeur :

Springer


Paru le : 2008-11-24

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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
Pages
439 pages
Collection
n.c
Parution
2008-11-24
Marque
Springer
EAN papier
9780387848150
EAN PDF
9780387848167
Informations sur l'ebook
Nombre pages copiables
4
Nombre pages imprimables
43
Taille du fichier
8591 Ko
Prix
94,94 €

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