Qingye Zhao — accepted AI-conference papers

2022

Wassertrain: An Adversarial Training Framework Against Wasserstein Adversarial Attacks

Qingye Zhao, Xin Chen, Zhuoyu Zhao, Enyi Tang, Xuandong Li

ICASSP 2022accepted

This paper presents an adversarial training framework WasserTrain for improving model robustness against the adversarial attacks in terms of the Wasserstein distance. First, an effective attack method WasserAttack is introduced with a novel encoding of the optimization problem, which directly finds…

Cited by 0 Source ↗Scholar ↗

2019

Robustness Verification of Classification Deep Neural Networks via Linear Programming

Wang Lin, Zhengfeng Yang, Xin Chen, Qingye Zhao, Xiangkun Li, Zhiming Liu +1

CVPR 2019poster

There is a pressing need to verify robustness of classification deep neural networks (CDNNs) as they are embedded in many safety-critical applications. Existing robustness verification approaches rely on computing the over-approximation of the output set, and can hardly scale up to practical CDNNs,…

Cited by 49 PDF ↗Scholar ↗