Adversarially Robust Self-Distillation
To mitigate the vulnerability of deep neural networks in the face of adversarial attacks, a variety of defense strategies have been proposed in recent years. Adversarially robust distillation provides an effective approach by transferring knowledge from a robust teacher model to a student model. However, most existing...