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Robust Out-of-distribution Detection via Informative Outlier Mining


Jun 26, 2020
Jiefeng Chen, Yixuan Li, Xi Wu, Yingyu Liang, Somesh Jha


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Representation Bayesian Risk Decompositions and Multi-Source Domain Adaptation


Apr 22, 2020
Xi Wu, Yang Guo, Jiefeng Chen, Yingyu Liang, Somesh Jha, Prasad Chalasani

* 25 pages, 6 figures 

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Robust Out-of-distribution Detection for Neural Networks


Apr 05, 2020
Jiefeng Chen, Yixuan Li, Xi Wu, Yingyu Liang, Somesh Jha


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Robust Out-of-distribution Detection in Neural Networks


Mar 24, 2020
Jiefeng Chen, Yixuan Li, Xi Wu, Yingyu Liang, Somesh Jha


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Query-Efficient Physical Hard-Label Attacks on Deep Learning Visual Classification


Feb 17, 2020
Ryan Feng, Jiefeng Chen, Nelson Manohar, Earlence Fernandes, Somesh Jha, Atul Prakash


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AI-GAN: Attack-Inspired Generation of Adversarial Examples


Feb 06, 2020
Tao Bai, Jun Zhao, Jinlin Zhu, Shoudong Han, Jiefeng Chen, Bo Li

* 7 pages, 6 figures. Submitted to IJCAI2020 

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Robust Attribution Regularization


May 23, 2019
Jiefeng Chen, Xi Wu, Vaibhav Rastogi, Yingyu Liang, Somesh Jha


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Reinforcing Adversarial Robustness using Model Confidence Induced by Adversarial Training


Jun 08, 2018
Xi Wu, Uyeong Jang, Jiefeng Chen, Lingjiao Chen, Somesh Jha

* To appear in ICML 2018 

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Improving Adversarial Robustness by Data-Specific Discretization


May 25, 2018
Jiefeng Chen, Xi Wu, Yingyu Liang, Somesh Jha


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ReabsNet: Detecting and Revising Adversarial Examples


Dec 21, 2017
Jiefeng Chen, Zihang Meng, Changtian Sun, Wei Tang, Yinglun Zhu


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