Zhuoxin Zhan

Accelerating Adversarial Training on Under-Utilized GPU

Deep neural networks are vulnerable to adversarial attacks and adversarial training has been proposed to defend against such attacks by adaptively generating attacks, i.e., adversarial examples, during training. However, adversarial training is significantly slower than traditional training due to t