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An introduction to computational learning theory

Author: Michael J Kearns; Umesh Virkumar Vazirani
Publisher: Cambridge, Mass. : MIT Press, ©1994.
Edition/Format:   Print book : EnglishView all editions and formats
Database:WorldCat
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Material Type: Internet resource
Document Type: Book, Internet Resource
All Authors / Contributors: Michael J Kearns; Umesh Virkumar Vazirani
ISBN: 0262111934 9780262111935
OCLC Number: 30476515
Description: xii, 207 p. : ill. ; 24 cm.
Contents: The probably approximately correct learning model --
Occam's razor --
The Vapnik-Chervonenkis dimension --
Weak and strong learning --
Learning in the presence of noise --
Inherent unpredictability --
Reducibility in PAC learning --
Learning finite automata by experimentation --
Appendix: some tools for probabilistic analysis.
Responsibility: Michael J. Kearns, Umesh V. Vazirani.

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