Robust Weight Perturbation for Adversarial Training

Understand

Overfitting widely exists in adversarial robust training of deep networks.

• An effective remedy is adversarial weight perturbation, which injects the worst-case weight perturbation during network training by maximizing the classification loss on adversarial examples.
• Adversarial weight perturbation helps reduce the robust generalization gap; however, it also undermines the robustness improvement.
• A criterion that regulates the weight perturbation is therefore crucial for adversarial training.