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cs.LG2021
Learning Defense Transformers for Counterattacking Adversarial Examples
Jincheng Li, Jiezhang Cao, Yifan Zhang +2
Deep neural networks (DNNs) are vulnerable to adversarial examples with small perturbations. Adversarial defense thus has been an important means which improves the robustness of D…
cs.LG2021★ 4 cited
Internal Wasserstein Distance for Adversarial Attack and Defense
Qicheng Wang, Shuhai Zhang, Jiezhang Cao +3
Deep neural networks (DNNs) are known to be vulnerable to adversarial attacks that would trigger misclassification of DNNs but may be imperceptible to human perception. Adversarial…