Computational Learning Theory (Cambridge Tracts in Theoretical Computer Science, Series Number 30) - Hardcover

Anthony, M. H. G.; Biggs, N.

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9780521416030: Computational Learning Theory (Cambridge Tracts in Theoretical Computer Science, Series Number 30)

Synopsis

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.

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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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