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Bounding sample size with the Vapnik-Chervonenkis dimension

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Publication:1209149
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DOI10.1016/0166-218X(93)90179-RzbMath0784.68070MaRDI QIDQ1209149

Martin Anthony, John Shawe-Taylor, Norman L. Biggs

Publication date: 16 May 1993

Published in: Discrete Applied Mathematics (Search for Journal in Brave)


zbMATH Keywords

Vapnik-Chervonenkis dimensionP.A.C


Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)


Related Items

A generalization of Sauer's lemma, An approach to guided learning of Boolean functions, Learning with side information: PAC learning bounds, PAC-learning from general examples, Using the doubling dimension to analyze the generalization of learning algorithms, Valid Generalisation from Approximate Interpolation, Combinatorics and connectionism, A result of Vapnik with applications



Cites Work

  • \(\epsilon\)-nets and simplex range queries
  • Quantifying inductive bias: AI learning algorithms and Valiant's learning framework
  • Learnability and the Vapnik-Chervonenkis dimension
  • A theory of the learnable
  • Computational limitations on learning from examples
  • On the Uniform Convergence of Relative Frequencies of Events to Their Probabilities
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