PeerAiD proposes a novel approach to adversarial distillation by training a peer network specialized in defending the student network, resulting in significantly higher robustness. The method improves both the robust accuracy and natural accuracy of the student network compared to various baselines.
PeerAiD proposes a novel method in adversarial distillation, training a peer network to defend against student-generated adversarial examples, achieving higher robustness and natural accuracy.
PeerAiD improves adversarial robustness by training a specialized peer network to defend against student-generated adversarial examples.