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A metric entropy bound is not sufficient for learnability

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3 Author(s)

The authors prove by means of a counterexample that it is not sufficient, for probably approximately correct (PAC) learning under a class of distributions, to have a uniform bound on the metric entropy of the class of concepts to be learned. This settles a conjecture of Benedek and Itai (1991)

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Information Theory, IEEE Transactions on  (Volume:40 ,  Issue: 3 )