Data Perturbation for Escaping Local Maxima in Learning

Abstract

Almost all machine learning algorithms--be they for regression, classification or density estimation--seek hypotheses that optimize a score on training data. In most interesting cases, however, full global optimization is not feasible and local search techniques are used to discover reasonable solutions. Unfortunately, the quality of the local maxima… (More)

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