EUR 76,84
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Aggiungi al carrelloCondizione: Acceptable. The book is 100% readable but visibly worn, and damaged. This may include stains, tears, rips, folded pages, binding damage, dents, scuffs, scratches and sticker residue. The book also may contain heavy highlighting and notes. Please ask for photos as our books are donations and may not contain above mentioned defects. There is a signature or handwriting on the inside front cover.
Editore: Springer-Verlag New York Inc., 2000
ISBN 10: 0387945598 ISBN 13: 9780387945590
Lingua: Inglese
Da: Ammareal, Morangis, Francia
Hardcover. Condizione: Bon. Ancien livre de bibliothèque avec équipements. Edition 2000. Ammareal reverse jusqu'à 15% du prix net de cet article à des organisations caritatives. ENGLISH DESCRIPTION Book Condition: Used, Good. Former library book. Edition 2000. Ammareal gives back up to 15% of this item's net price to charity organizations.
Da: BooksRun, Philadelphia, PA, U.S.A.
EUR 138,47
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Aggiungi al carrelloHardcover. Condizione: Fair. 2nd. The item might be beaten up but readable. May contain markings or highlighting, as well as stains, bent corners, or any other major defect, but the text is not obscured in any way.
Da: BooksRun, Philadelphia, PA, U.S.A.
EUR 138,47
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Aggiungi al carrelloHardcover. Condizione: Good. 2nd. It's a preowned item in good condition and includes all the pages. It may have some general signs of wear and tear, such as markings, highlighting, slight damage to the cover, minimal wear to the binding, etc., but they will not affect the overall reading experience.
Da: HPB-Red, Dallas, TX, U.S.A.
EUR 138,45
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Aggiungi al carrellohardcover. Condizione: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!
Da: Solr Books, Lincolnwood, IL, U.S.A.
EUR 141,96
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Aggiungi al carrelloCondizione: very_good. This books is in Very good condition. There may be a few flaws like shelf wear and some light wear.
Da: BennettBooksLtd, North Las Vegas, NV, U.S.A.
EUR 167,89
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Aggiungi al carrellohardcover. Condizione: New. In shrink wrap. Looks like an interesting title!
EUR 217,43
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EUR 219,76
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EUR 221,94
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Da: Best Price, Torrance, CA, U.S.A.
EUR 217,25
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Da: Best Price, Torrance, CA, U.S.A.
EUR 217,25
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EUR 211,37
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Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 218,47
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Da: Lucky's Textbooks, Dallas, TX, U.S.A.
EUR 228,84
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EUR 218,46
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Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 226,89
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Aggiungi al carrelloCondizione: New. In English.
EUR 241,97
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Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.
EUR 189,69
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Aggiungi al carrelloCondizione: New. The aim of this book is to discuss the fundamental ideas which lie behind the statistical theory of learning and generalization. Written in readable and concise style and devoted to key learning problems, the book is intended for statisticians, mathematicia.
Da: California Books, Miami, FL, U.S.A.
EUR 258,53
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Da: California Books, Miami, FL, U.S.A.
EUR 258,53
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Aggiungi al carrelloCondizione: New.
EUR 241,90
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Editore: Springer-Verlag New York Inc., US, 1999
ISBN 10: 0387987800 ISBN 13: 9780387987804
Lingua: Inglese
Da: Rarewaves.com USA, London, LONDO, Regno Unito
EUR 311,35
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Aggiungi al carrelloHardback. Condizione: New. Second Edition 2000. The aim of this book is to discuss the fundamental ideas which lie behind the statistical theory of learning and generalization. It considers learning as a general problem of function estimation based on empirical data. Omitting proofs and technical details, the author concentrates on discussing the main results of learning theory and their connections to fundamental problems in statistics. These include: * the setting of learning problems based on the model of minimizing the risk functional from empirical data * a comprehensive analysis of the empirical risk minimization principle including necessary and sufficient conditions for its consistency * non-asymptotic bounds for the risk achieved using the empirical risk minimization principle * principles for controlling the generalization ability of learning machines using small sample sizes based on these bounds * the Support Vector methods that control the generalization ability when estimating function using small sample size. The second edition of the book contains three new chapters devoted to further development of the learning theory and SVM techniques. These include: * the theory of direct method of learning based on solving multidimensional integral equations for density, conditional probability, and conditional density estimation * a new inductive principle of learning. Written in a readable and concise style, the book is intended for statisticians, mathematicians, physicists, and computer scientists. Vladimir N. Vapnik is Technology Leader ATandT Labs-Research and Professor of London University. He is one of the founders of.
EUR 311,30
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Aggiungi al carrelloHardcover. Condizione: new. Excellent Condition.Excels in customer satisfaction, prompt replies, and quality checks.
Editore: Springer New York, Springer US, 2010
ISBN 10: 1441931600 ISBN 13: 9781441931603
Lingua: Inglese
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 249,24
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - The aim of this book is to discuss the fundamental ideas which lie behind the statistical theory of learning and generalization. It considers learning as a general problem of function estimation based on empirical data. Omitting proofs and technical details, the author concentrates on discussing the main results of learning theory and their connections to fundamental problems in statistics. These include: \* the setting of learning problems based on the model of minimizing the risk functional from empirical data \* a comprehensive analysis of the empirical risk minimization principle including necessary and sufficient conditions for its consistency \* non-asymptotic bounds for the risk achieved using the empirical risk minimization principle \* principles for controlling the generalization ability of learning machines using small sample sizes based on these bounds \* the Support Vector methods that control the generalization ability when estimating function using small sample size. The second edition of the book contains three new chapters devoted to further development of the learning theory and SVM techniques. These include: \* the theory of direct method of learning based on solving multidimensional integral equations for density, conditional probability, and conditional density estimation \* a new inductive principle of learning. Written in a readable and concise style, the book is intended for statisticians, mathematicians, physicists, and computer scientists. Vladimir N. Vapnik is Technology Leader AT&T Labs-Research and Professor of London University. He is one of the founders of.
EUR 320,54
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Aggiungi al carrelloCondizione: New. pp. 340 2nd Edition.
EUR 321,95
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Aggiungi al carrelloCondizione: New. pp. 336 2nd Edition.
Da: Mispah books, Redhill, SURRE, Regno Unito
EUR 339,34
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Aggiungi al carrelloPaperback. Condizione: Like New. Like New. book.
EUR 348,82
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Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.