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

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

Hardcover

ISBN 10: 0521416035 ISBN 13: 9780521416030

Publisher: Cambridge University Press, 1992

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.

About this title

Review

."..clean, readable, self-contained treatment of the foundations of PAC learnability theory." R. Roos, Computing Reviews ."..notable for its clean, readable, self-contained treatment of the foundations of PAC learnability theory." R. Roos, Artificial Intelligence ."..a welcome addition to the limited range of literature on computational learning theory, and it should perform a useful service in alerting a wider audience to this interesting and lively area..." Mathematical reviews

Book Description

This is a self contained volume in which the authors concentrate on the 'probably approximately correct model'. 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.

Edition details

• Publisher: Cambridge University Press
• Publication date: 1992
• ISBN 10: 0521416035
• ISBN 13: 9780521416030
• Binding: Hardcover
• Language: English
• Number of pages: 171