Sample Complexity of Smooth Stochastic Optimization∗


Let N( , δ) be the number of samples needed when solving a stochastic program such that the objective function evaluated at the sample optimizer is within of the true optimum with probability 1− δ. Previous results are of the form N( , δ) = O( −2 log δ−1). However, a smooth objective function is often locally quadratic at an interior optimum. For that case… (More)


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