Learning Boolean Functions in an Infinite Attribute Space Learning Boolean Functions in an Infinite Attribute Space
Paper summary This paper develops algorithms and mistake bounds for learning non-noisy boolean functions. It considers the case when there is a very large number of possible attributes, but each example (and the concept) depends on only a few attributes, so we want ot avoid having to ever explicitly list or consider all possible attributes. The concept classes it deals with learning are boolean formulas. The paper is a good cite but (for my work) probably not directly applicable.
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Learning Boolean Functions in an Infinite Attribute Space
Blum, Avrim
Machine Learning Journal - 1992 via Bibsonomy
Keywords: dblp


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