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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:   eBook : EnglishView all editions and formats
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Kearns, Michael J.
Introduction to computational learning theory.
Cambridge, Mass. : MIT Press, ©1994
(DLC) 94016588
(OCoLC)30476515
Material Type: Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Michael J Kearns; Umesh Virkumar Vazirani
ISBN: 0585350531 9780585350530 0262276860 9780262276863
OCLC Number: 47009798
Description: 1 online resource (xii, 207 pages) : illustrations
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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