Learning with a Strong Adversary

10 Nov 2015Ruitong HuangBing XuDale SchuurmansCsaba Szepesvari

The robustness of neural networks to intended perturbations has recently attracted significant attention. In this paper, we propose a new method, \emph{learning with a strong adversary}, that learns robust classifiers from supervised data... (read more)

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