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Computational Learning Theory (Cambridge Tracts in Theoretical Computer Science, Series Number 30) - Softcover
Synopsis
Computational learning theory is one of the first attempts to construct a mathematical theory of a cognitive process. It has been a field of much interest and rapid growth in recent years. This text provides a framework for studying a variety of algorithmic processes, such as those currently in use for training artificial neural networks. The authors concentrate on an approximate model for learning and gradually develop the ideas of efficiency considerations. Finally, they consider applications of the theory to artificial neural networks. An abundance of exercises and an extensive list of references round out the text. This volume provides a comprehensive review of the topic, including information drawn from logic, probability, and complexity theory. It forms a solid introduction to the theory of comptutational learning suitable for a broad spectrum of graduate students from theoretical computer science to mathematics.
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Book Description
Computational learning theory is a subject which has been advancing rapidly in the last few years. The authors concentrate on the probably approximately correct model of learning, and gradually develop the ideas of efficiency considerations. Finally, applications of the theory to artificial neural networks are considered. Many exercises are included throughout, and the list of references is extensive. This volume is relatively self contained as the necessary background material from logic, probability and complexity theory is included. It will therefore form an introduction to the theory of computational learning, suitable for a broad spectrum of graduate students from theoretical computer science and mathematics.
About the Author
John Shawe-Taylor, Department of Computer Science, Royal Holloway, University of London. Martin Anthony, Lecturer in Mathematics, London School of Economics and Political Science.
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- PublisherCambridge University Press
- Publication date1997
- ISBN 10 0521599229
- ISBN 13 9780521599221
- BindingPaperback
- LanguageEnglish
- Number of pages172
- Rating
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Computational Learning Theory (Cambridge Tracts in Theoretical Computer Science, Series Number 30)
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ISBN 13: 9780521599221
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Computational Learning Theory (Cambridge Tracts in Theoretical Computer Science, Series Number 30)
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ISBN 10: 0521599229
ISBN 13: 9780521599221
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Computational Learning Theory
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ISBN 13: 9780521599221
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Computational Learning Theory (Cambridge Tracts in Theoretical Computer Science, Series Number 30)
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ISBN 13: 9780521599221
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Computational Learning Theory (Cambridge Tracts in Theoretical Computer Science, Series Number 30)
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ISBN 13: 9780521599221
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Computational Learning Theory (Paperback)
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ISBN 13: 9780521599221
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Paperback. Condition: new. Paperback. Computational learning theory is a subject which has been advancing rapidly in the last few years. The authors concentrate on the probably approximately correct model of learning, and gradually develop the ideas of efficiency considerations. Finally, applications of the theory to artificial neural networks are considered. Many exercises are included throughout, and the list of references is extensive. This volume is relatively self contained as the necessary background material from logic, probability and complexity theory is included. It will therefore form an introduction to the theory of computational learning, suitable for a broad spectrum of graduate students from theoretical computer science and mathematics. Computational learning theory is one of the first attempts to construct a mathematical theory of a cognitive process. It has been a field of much interest and rapid growth in recent years. This text provides a framework for studying a variety of algorithmic processes, such as those currently in use for training artificial neural networks. The authors concentrate on an approximate model for learning and gradually develop the ideas of efficiency considerations. Finally, they consider applications of the theory to artificial neural networks. An abundance of exercises and an extensive list of references round out the text. This volume provides a comprehensive review of the topic, including information drawn from logic, probability, and complexity theory. It forms a solid introduction to the theory of comptutational learning suitable for a broad spectrum of graduate students from theoretical computer science to mathematics. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9780521599221
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Computational Learning Theory
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ISBN 13: 9780521599221
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Computational Learning Theory: An Introduction
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Computational Learning Theory
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