Hung-Jui Wang

Annealing Self-Distillation Rectification Improves Adversarial Training

In standard adversarial training, models are optimized to fit invariant one-hot labels for adversarial data when the perturbations are within allowable budgets. However, the overconfident target harms generalization and causes the problem of robust overfitting. To address this issue and enhance adve…