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Smoothed Online Convex Optimization Based on Discounted-Normal-Predictor



Lijun Zhang , Wei Jiang , Jinfeng Yi , Tianbao Yang


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How to Robustify Black-Box ML Models? A Zeroth-Order Optimization Perspective



Yimeng Zhang , Yuguang Yao , Jinghan Jia , Jinfeng Yi , Mingyi Hong , Shiyu Chang , Sijia Liu

* Accepted as ICLR'22 Spotlight Paper 

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Can Adversarial Training Be Manipulated By Non-Robust Features?



Lue Tao , Lei Feng , Hongxin Wei , Jinfeng Yi , Sheng-Jun Huang , Songcan Chen


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On the Convergence and Robustness of Adversarial Training



Yisen Wang , Xingjun Ma , James Bailey , Jinfeng Yi , Bowen Zhou , Quanquan Gu

* ICML 2019 Long Talk. Fixing bugs in the proof of Theorem 1 

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Federated Two-stage Learning with Sign-based Voting



Zichen Ma , Zihan Lu , Yu Lu , Wenye Li , Jinfeng Yi , Shuguang Cui

* Preprint, the first version is accomplished in 02/2020 

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How and When Adversarial Robustness Transfers in Knowledge Distillation?



Rulin Shao , Jinfeng Yi , Pin-Yu Chen , Cho-Jui Hsieh


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Adversarial Attack across Datasets



Yunxiao Qin , Yuanhao Xiong , Jinfeng Yi , Cho-Jui Hsieh


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Trustworthy AI: From Principles to Practices



Bo Li , Peng Qi , Bo Liu , Shuai Di , Jingen Liu , Jiquan Pei , Jinfeng Yi , Bowen Zhou


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Training Meta-Surrogate Model for Transferable Adversarial Attack



Yunxiao Qin , Yuanhao Xiong , Jinfeng Yi , Cho-Jui Hsieh

* 15 pages, 7 figures 

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Understanding Clipping for Federated Learning: Convergence and Client-Level Differential Privacy



Xinwei Zhang , Xiangyi Chen , Mingyi Hong , Zhiwei Steven Wu , Jinfeng Yi


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