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cs.LG2021
Bridged Adversarial Training
Hoki Kim, Woojin Lee, Sungyoon Lee +1
Adversarial robustness is considered as a required property of deep neural networks. In this study, we discover that adversarially trained models might have significantly different…
cs.LG2021★ 2 cited
GradDiv: Adversarial Robustness of Randomized Neural Networks via Gradient Diversity Regularization
Sungyoon Lee, Hoki Kim, Jaewook Lee
Deep learning is vulnerable to adversarial examples. Many defenses based on randomized neural networks have been proposed to solve the problem, but fail to achieve robustness again…