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To be Robust or to be Fair: Towards Fairness in Adversarial Training

Oct 13, 2020
Han Xu, Xiaorui Liu, Yaxin Li, Jiliang Tang


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Yet Meta Learning Can Adapt Fast, It Can Also Break Easily

Sep 02, 2020
Han Xu, Yaxin Li, Xiaorui Liu, Hui Liu, Jiliang Tang

* Meta Learning Robustnss 

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DeepRobust: A PyTorch Library for Adversarial Attacks and Defenses

May 13, 2020
Yaxin Li, Wei Jin, Han Xu, Jiliang Tang

* Adversarial attacks and defenses, Pytorch library 

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Adversarial Attacks and Defenses on Graphs: A Review and Empirical Study

Mar 03, 2020
Wei Jin, Yaxin Li, Han Xu, Yiqi Wang, Jiliang Tang

* 22 pages, 7 figures 

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Collaborative Attention Network for Person Re-identification

Nov 29, 2019
Wenpeng Li, Yongli Sun, Jinjun Wang, Han Xu, Xiangru Yang, Long Cui


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Adversarial Attacks and Defenses in Images, Graphs and Text: A Review

Oct 09, 2019
Han Xu, Yao Ma, Haochen Liu, Debayan Deb, Hui Liu, Jiliang Tang, Anil K. Jain

* survey, adversarial attacks, defenses 

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Covariance-Insured Screening

May 17, 2018
Kevin He, Jian Kang, Hyokyoung Grace Hong, Ji Zhu, Yanming Li, Huazhen Lin, Han Xu, Yi Li


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