26 citations · 48 across the 6 of their papers we have counts for
Showing 2020Show all
2 papers · 1 filter
cs.LG2020★ 2 cited
Blind Adversarial Training: Balance Accuracy and Robustness
Haidong Xie, Xueshuang Xiang, Naijin Liu +1
Adversarial training (AT) aims to improve the robustness of deep learning models by mixing clean data and adversarial examples (AEs). Most existing AT approaches can be grouped int…
cs.LG2020
Blind Adversarial Pruning: Balance Accuracy, Efficiency and Robustness
Haidong Xie, Lixin Qian, Xueshuang Xiang +1
With the growth of interest in the attack and defense of deep neural networks, researchers are focusing more on the robustness of applying them to devices with limited memory. Thus…