Bounding sample size with the Vapnik-Chervonenkis dimension
From MaRDI portal
Publication:1209149
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)
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