Sinossi
"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
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Dalla quarta di copertina
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
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
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Information Theory and Statistical Learning
Da: Lucky's Textbooks, Dallas, TX, U.S.A.
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Information Theory and Statistical Learning
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -'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 452 pp. Englisch. Codice articolo 9781441946508
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Information Theory and Statistical Learning
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Information Theory and Statistical Learning
Print on DemandDa: moluna, Greven, Germania
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Combines information theory and statistical learning components in one volumeMany chapters are contributed by authors that pioneered the presented methods themselvesInterdisciplinary approach makes this book accessible to researchers and pr. Codice articolo 4174983
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Information Theory and Statistical Learning
Editore:
Springer US, Springer US Nov 2010, 2010
ISBN 10: 1441946500
ISBN 13: 9781441946508
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -'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 TokyoSpringer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 452 pp. Englisch. Codice articolo 9781441946508
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Information Theory and Statistical Learning
Editore:
Springer US, Springer US, 2010
ISBN 10: 1441946500
ISBN 13: 9781441946508
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Da: AHA-BUCH GmbH, Einbeck, Germania
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Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - '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. Codice articolo 9781441946508
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