Probably Approximate Learning over Classes of Distributions

DOI10.1137/0221029zbMath0761.68080OpenAlexW2042672920MaRDI QIDQ4016907

B. K. Natarajan

Publication date: 16 January 1993

Published in: SIAM Journal on Computing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1137/0221029

zbMATH Keywords

setsfunctionsprobabilistic learningclasses of distributions

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Nonparametric inference (62G99)

Related Items (5)

PAC learning of probability distributions over a discrete domain. ⋮ Decision theoretic generalizations of the PAC model for neural net and other learning applications ⋮ Learning dynamical systems in a stationary environment ⋮ Sample size lower bounds in PAC learning by Algorithmic Complexity Theory ⋮ Learnability with respect to fixed distributions

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