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Xiaodan Li

Rethinking Out-of-Distribution Detection From a Human-Centric Perspective

Nov 30, 2022
Yao Zhu, Yuefeng Chen, Xiaodan Li, Rong Zhang, Hui Xue, Xiang Tian, Rongxin Jiang, Bolun Zheng, Yaowu Chen

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* Preprint version. Submitted to International Journal of Computer Vision

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Towards Understanding and Boosting Adversarial Transferability from a Distribution Perspective

Oct 09, 2022
Yao Zhu, Yuefeng Chen, Xiaodan Li, Kejiang Chen, Yuan He, Xiang Tian, Bolun Zheng, Yaowu Chen, Qingming Huang

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* \copyright 20XX IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works

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MaxMatch: Semi-Supervised Learning with Worst-Case Consistency

Sep 26, 2022
Yangbangyan Jiang, Xiaodan Li, Yuefeng Chen, Yuan He, Qianqian Xu, Zhiyong Yang, Xiaochun Cao, Qingming Huang

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* Accepted to IEEE TPAMI

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Enhance the Visual Representation via Discrete Adversarial Training

Sep 16, 2022
Xiaofeng Mao, Yuefeng Chen, Ranjie Duan, Yao Zhu, Gege Qi, Shaokai Ye, Xiaodan Li, Rong Zhang, Hui Xue

* Accepted to NeurIPS 2022, https://github.com/alibaba/easyrobust

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Beyond ImageNet Attack: Towards Crafting Adversarial Examples for Black-box Domains

Feb 10, 2022
Qilong Zhang, Xiaodan Li, Yuefeng Chen, Jingkuan Song, Lianli Gao, Yuan He, Hui Xue

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* Accepted by ICLR 2022

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