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SoK: Certified Robustness for Deep Neural Networks. (arXiv:2009.04131v7 [cs.LG] UPDATED)
Aug. 24, 2022, 1:20 a.m. | Linyi Li, Tao Xie, Bo Li
cs.CR updates on arXiv.org arxiv.org
Great advances in deep neural networks (DNNs) have led to state-of-the-art
performance on a wide range of tasks. However, recent studies have shown that
DNNs are vulnerable to adversarial attacks, which have brought great concerns
when deploying these models to safety-critical applications such as autonomous
driving. Different defense approaches have been proposed against adversarial
attacks, including: a) empirical defenses, which can usually be adaptively
attacked again without providing robustness certification; and b) certifiably
robust approaches, which consist of robustness verification …
More from arxiv.org / cs.CR updates on arXiv.org
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