Web: http://arxiv.org/abs/2209.07369

Sept. 16, 2022, 1:12 a.m. | Omar Montasser, Steve Hanneke, Nathan Srebro

cs.LG updates on arXiv.org arxiv.org

We present a minimax optimal learner for the problem of learning predictors
robust to adversarial examples at test-time. Interestingly, we find that this
requires new algorithmic ideas and approaches to adversarially robust learning.
In particular, we show, in a strong negative sense, the suboptimality of the
robust learner proposed by Montasser, Hanneke, and Srebro (2019) and a broader
family of learners we identify as local learners. Our results are enabled by
adopting a global perspective, specifically, through a key technical …

arxiv minimax

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