On PAC learning algorithms for rich boolean function classes

Authors:
Rocco A. Servedio
Affiliations:
Department of Computer Science, Columbia University, New York
Venue:
TAMC'06 Proceedings of the Third international conference on Theory and Applications of Models of Computation
Year:
2006

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Abstract

We survey the fastest known algorithms for learning various expressive classes of Boolean functions in the Probably Approximately Correct (PAC) learning model.