Sharp Statistical Guarantees for Adversarially Robust Gaussian Classification

ICML, pp. 2345-2355, 2020.

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Abstract:

Adversarial robustness has become a fundamental requirement in modern machine learning applications. Yet, there has been surprisingly little statistical understanding so far. In this paper, we provide the first result of the optimal minimax guarantees for the excess risk for adversarially robust classification, under Gaussian mixture mo...More

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