Synopsis
This book describes theoretical advances in the study of artificial neural networks.
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Neural Network Learning This book describes theoretical advances in the study of artificial neural networks. Full description
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
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Neural Network Learning: Theoretical Foundations
Published by
Cambridge University Press, 2009
ISBN 10: 052111862X
ISBN 13: 9780521118620
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Neural Network Learning: Theoretical Foundations
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Cambridge University Press, 2009
ISBN 10: 052111862X
ISBN 13: 9780521118620
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Neural Network Learning: Theoretical Foundations
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Neural Network Learning : Theoretical Foundations
Published by
Cambridge University Press, 2009
ISBN 10: 052111862X
ISBN 13: 9780521118620
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Neural Network Learning (Paperback)
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Cambridge University Press, Cambridge, 2009
ISBN 10: 052111862X
ISBN 13: 9780521118620
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Paperback. Condition: new. Paperback. 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. Research on pattern classification with binary-output networks is surveyed, including a discussion of the relevance of the VapnikChervonenkis dimension, and calculating estimates of the dimension for several neural network models. A model of classification by real-output networks is developed, and the usefulness of classification with a 'large margin' is demonstrated. The authors explain the role of scale-sensitive versions of the VapnikChervonenkis dimension in large margin classification, and in real prediction. They 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 is intended to be accessible to researchers and graduate students in computer science, engineering, and mathematics. 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. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9780521118620
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Neural Network Learning: Theoretical Foundations
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ISBN 10: 052111862X
ISBN 13: 9780521118620
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Neural Network Learning: Theoretical Foundations
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Cambridge University Press 2009-08-28, 2009
ISBN 10: 052111862X
ISBN 13: 9780521118620
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Neural Network Learning
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ISBN 13: 9780521118620
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Neural Network Learning : Theoretical Foundations
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ISBN 13: 9780521118620
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Neural Network Learning: Theoretical Foundations
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ISBN 13: 9780521118620
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