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A unified approach is taken for deriving new generalization data dependent bounds for several classes of algorithms explored in the existing literature by different approaches. This unified approach is based on an extension of Vapnik's inequality for VC classes of sets to random classes of sets-that is, classes depending on the random data, invariant under(More)
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