Revisiting Adversarial Robustness Distillation: Robust Soft Labels Make
Student Better
Revisiting Adversarial Robustness Distillation: Robust Soft Labels Make
Student Better
Adversarial training is one effective approach for training robust deep neural networks against adversarial attacks. While being able to bring reliable robustness, adversarial training (AT) methods in general favor high capacity models, i.e., the larger the model the better the robustness. This tends to limit their effectiveness on small models, …