Items related to Neural Network Learning: Theoretical Foundations
Synopsis
This book describes theoretical advances in the study of artificial neural networks.
"synopsis" may belong to another edition of this title.
Review
'The book is a useful and readable mongraph. For beginners it is a nice introduction to the subject, for experts a valuable reference.' Zentralblatt MATH
Book Description
This book describes theoretical advances in the study of artificial neural networks. It explores probabilistic models of supervised learning problems, and addresses the key statistical and computational questions. It is intended to be accessible to researchers and graduate students in computer science, engineering, and mathematics.
"About this title" may belong to another edition of this title.
Search results for Neural Network Learning: Theoretical Foundations
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Neural Network Learning : Theoretical Foundations
Published by
Cambridge University Press, 1999
ISBN 10: 052157353X
ISBN 13: 9780521573535
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Neural Network Learning
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Cambridge University Press, 2015
ISBN 10: 052157353X
ISBN 13: 9780521573535
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Neural network learning theoretical foundations Martin Anthony and Peter L. Bartlett.
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Cambridge, Cambridge University Press, 1999
ISBN 10: 052157353X
ISBN 13: 9780521573535
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Hardcover. Ex-library with stamp and library-signature. GOOD condition, some traces of use. Ancien Exemplaire de bibliothèque avec signature et cachet. BON état, quelques traces d'usure. Ehem. Bibliotheksexemplar mit Signatur und Stempel. GUTER Zustand, ein paar Gebrauchsspuren. 68 ANT 9780521573535 Sprache: Englisch Gewicht in Gramm: 1150. Seller Inventory # 2499879
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Neural network learning theoretical foundations Martin Anthony and Peter L. Bartlett.
Published by
Cambridge, Cambridge University Press, 1999
ISBN 10: 052157353X
ISBN 13: 9780521573535
Used
Hardcover
Seller: Antiquariat Bookfarm, Löbnitz, Germany
Seller rating 5 out of 5 stars
Hardcover. Ex-library with stamp and library-signature. GOOD condition, some traces of use. Ancien Exemplaire de bibliothèque avec signature et cachet. BON état, quelques traces d'usure. Ehem. Bibliotheksexemplar mit Signatur und Stempel. GUTER Zustand, ein paar Gebrauchsspuren. C 1170: (1999) 9780521573535 Sprache: Englisch Gewicht in Gramm: 1150. Seller Inventory # 2504569
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Neural Network Learning: Theoretical Foundations
Published by
Cambridge University Press, 1999
ISBN 10: 052157353X
ISBN 13: 9780521573535
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Condition: Good. Your purchase helps support Sri Lankan Children's Charity 'The Rainbow Centre'. Ex-library, so some stamps and wear, but in good overall condition. Our donations to The Rainbow Centre have helped provide an education and a safe haven to hundreds of children who live in appalling conditions. Seller Inventory # Z1-X-027-02420
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Neural Network Learning: Theoretical Foundations
Published by
Cambridge University Press, 1999
ISBN 10: 052157353X
ISBN 13: 9780521573535
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Condition: Acceptable. Readable, but has significant damage / tears. Has a remainder mark. hardcover Used - Acceptable 1999. Seller Inventory # AB-002119
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Neural Network Learning : Theoretical Foundations
Published by
Cambridge University Press, 1999
ISBN 10: 052157353X
ISBN 13: 9780521573535
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Neural Network Learning: Theoretical Foundations
Published by
Cambridge University Press, 1999
ISBN 10: 052157353X
ISBN 13: 9780521573535
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Neural Network Learning (Hardcover)
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Cambridge University Press, Cambridge, 1999
ISBN 10: 052157353X
ISBN 13: 9780521573535
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First Edition
Seller: CitiRetail, Stevenage, United Kingdom
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Hardcover. Condition: new. Hardcover. This important work describes recent theoretical advances in the study of artificial neural networks. It explores probabilistic models of supervised learning problems, and addresses the key statistical and computational questions. Chapters survey research on pattern classification with binary-output networks, including a discussion of the relevance of the Vapnik Chervonenkis dimension, and of estimates of the dimension for several neural network models. In addition, Anthony and Bartlett develop a model of classification by real-output networks, and demonstrate the usefulness of classification with a "large margin." The authors explain the role of scale-sensitive versions of the Vapnik Chervonenkis dimension in large margin classification, and in real prediction. Key chapters also discuss the computational complexity of neural network learning, describing a variety of hardness results, and outlining two efficient, constructive learning algorithms. The book is self-contained and accessible to researchers and graduate students in computer science, engineering, and mathematics. This important work describes recent theoretical advances in the study of artificial neural networks. It explores probabilistic models of supervised learning problems, and addresses the key statistical and computational questions. Chapters survey research on pattern classification with binary-output networks, including a discussion of the relevance of the Vapnik Chervonenkis dimension, and of estimates of the dimension for several neural network models. In addition, Anthony and Bartlett develop a model of classification by real-output networks, and demonstrate the usefulness of classification with a "large margin." The authors explain the role of scale-sensitive versions of the Vapnik Chervonenkis dimension in large margin classification, and in real prediction. Key chapters also discuss the computational complexity of neural network learning, describing a variety of hardness results, and outlining two efficient, constructive learning algorithms. The book is self-contained and accessible to researchers and graduate students in computer science, engineering, and mathematics. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9780521573535
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Neural Network Learning: Theoretical Foundations
Published by
Cambridge University Press, 1999
ISBN 10: 052157353X
ISBN 13: 9780521573535
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Hardcover
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Hardback. Condition: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 709. Seller Inventory # C9780521573535
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