A sufficient condition for polynomial distribution-dependent learnability
From MaRDI portal
Publication:1364775
DOI10.1016/S0166-218X(96)00129-1zbMath0888.68103OpenAlexW2058287499WikidataQ126653792 ScholiaQ126653792MaRDI QIDQ1364775
Martin Anthony, John Shawe-Taylor
Publication date: 1 June 1998
Published in: Discrete Applied Mathematics (Search for Journal in Brave)
Full work available at URL: http://www.elsevier.com/locate/dam
Cites Work
- Unnamed Item
- Unnamed Item
- Learnability with respect to fixed distributions
- Quantifying inductive bias: AI learning algorithms and Valiant's learning framework
- A parameterization scheme for classifying models of PAC learnability
- Queries and concept learning
- On the density of families of sets
- Probably Approximate Learning of Sets and Functions
- Learnability and the Vapnik-Chervonenkis dimension
- A theory of the learnable
- On the Uniform Convergence of Relative Frequencies of Events to Their Probabilities
- Convergence of stochastic processes
This page was built for publication: A sufficient condition for polynomial distribution-dependent learnability
