Robust Local Features for Improving the Generalization of Adversarial Training

Chuanbiao Song, Kun He, Jiadong Lin, Liwei Wang, John E. Hopcroft

Abstract: We propose a new stream of adversarial training approach called Robust Local Features for Adversarial Training (RLFAT) that significantly improves both the adversarially robust generalization and the standard generalization.