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Max Losch

1 accepted papers

2024

On Adversarial Training without Perturbing all Examples

ICLR 2024poster

Adversarial training is the de-facto standard for improving robustness against adversarial examples. This usually involves a multi-step adversarial attack applied on each example during training. In this paper, we explore only constructing adversarial examples (AE) on a subset of the training exampl…