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The Resource An introduction to computational learning theory, Michael J. Kearns, Umesh V. Vazirani, (electronic book)

An introduction to computational learning theory, Michael J. Kearns, Umesh V. Vazirani, (electronic book)

Label
An introduction to computational learning theory
Title
An introduction to computational learning theory
Statement of responsibility
Michael J. Kearns, Umesh V. Vazirani
Creator
Contributor
Subject
Language
eng
Member of
Cataloging source
N$T
http://library.link/vocab/creatorName
Kearns, Michael J
Dewey number
006.3
Illustrations
illustrations
Index
index present
LC call number
Q325.5
LC item number
.K44 1994eb
Literary form
non fiction
Nature of contents
  • standards specifications
  • bibliography
http://library.link/vocab/relatedWorkOrContributorName
Vazirani, Umesh Virkumar
http://library.link/vocab/subjectName
  • Machine learning
  • Artificial intelligence
  • Algorithms
  • Neural networks (Computer science)
  • Apprentissage automatique
  • Intelligence artificielle
  • Algorithmes
  • Réseaux neuronaux (Informatique)
Label
An introduction to computational learning theory, Michael J. Kearns, Umesh V. Vazirani, (electronic book)
Instantiates
Publication
Bibliography note
Includes bibliographical references (p. [193]-203) and index
Color
multicolored
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
Control code
IEEEMIT47009798
Dimensions
unknown
Extent
1 online resource (xii, 207 p.)
Form of item
online
Isbn
9780585350530
Other physical details
ill.
Reproduction note
Electronic resource.
Specific material designation
remote
System control number
ocm47009798
Label
An introduction to computational learning theory, Michael J. Kearns, Umesh V. Vazirani, (electronic book)
Publication
Bibliography note
Includes bibliographical references (p. [193]-203) and index
Color
multicolored
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
Control code
IEEEMIT47009798
Dimensions
unknown
Extent
1 online resource (xii, 207 p.)
Form of item
online
Isbn
9780585350530
Other physical details
ill.
Reproduction note
Electronic resource.
Specific material designation
remote
System control number
ocm47009798

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