Geometry-Inspired Top-k Adversarial Perturbations

28 Jun 2020Nurislam TursynbekAleksandr PetiushkoIvan Oseledets

State-of-the-art deep learning models are untrustworthy due to their vulnerability to adversarial examples. Intriguingly, besides simple adversarial perturbations, there exist Universal Adversarial Perturbations (UAPs), which are input-agnostic perturbations that lead to misclassification of majority inputs... (read more)

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