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Understanding and Improving Early Stopping for Learning with Noisy Labels


Jun 30, 2021
Yingbin Bai, Erkun Yang, Bo Han, Yanhua Yang, Jiatong Li, Yinian Mao, Gang Niu, Tongliang Liu

* 19 pages, 5 figures 

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Local Reweighting for Adversarial Training


Jun 30, 2021
Ruize Gao, Feng Liu, Kaiwen Zhou, Gang Niu, Bo Han, James Cheng


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Multi-Class Classification from Single-Class Data with Confidences


Jun 16, 2021
Yuzhou Cao, Lei Feng, Senlin Shu, Yitian Xu, Bo An, Gang Niu, Masashi Sugiyama

* 23 pages, 1 figure 

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Probabilistic Margins for Instance Reweighting in Adversarial Training


Jun 15, 2021
Qizhou Wang, Feng Liu, Bo Han, Tongliang Liu, Chen Gong, Gang Niu, Mingyuan Zhou, Masashi Sugiyama

* 17 pages, 4 figures 

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Adversarial Robustness through the Lens of Causality


Jun 11, 2021
Yonggang Zhang, Mingming Gong, Tongliang Liu, Gang Niu, Xinmei Tian, Bo Han, Bernhard Schölkopf, Kun Zhang


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On the Robustness of Average Losses for Partial-Label Learning


Jun 11, 2021
Jiaqi Lv, Lei Feng, Miao Xu, Bo An, Gang Niu, Xin Geng, Masashi Sugiyama


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Reliable Adversarial Distillation with Unreliable Teachers


Jun 09, 2021
Jianing Zhu, Jiangchao Yao, Bo Han, Jingfeng Zhang, Tongliang Liu, Gang Niu, Jingren Zhou, Jianliang Xu, Hongxia Yang


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Understanding (Generalized) Label Smoothing when Learning with Noisy Labels


Jun 09, 2021
Jiaheng Wei, Hangyu Liu, Tongliang Liu, Gang Niu, Yang Liu

* Under Review 

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Understanding (Generalized) Label Smoothing whenLearning with Noisy Labels


Jun 08, 2021
Jiaheng Wei, Hangyu Liu, Tongliang Liu, Gang Niu, Yang Liu

* Under Review 

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Instance Correction for Learning with Open-set Noisy Labels


Jun 01, 2021
Xiaobo Xia, Tongliang Liu, Bo Han, Mingming Gong, Jun Yu, Gang Niu, Masashi Sugiyama


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Sample Selection with Uncertainty of Losses for Learning with Noisy Labels


Jun 01, 2021
Xiaobo Xia, Tongliang Liu, Bo Han, Mingming Gong, Jun Yu, Gang Niu, Masashi Sugiyama


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NoiLIn: Do Noisy Labels Always Hurt Adversarial Training?


May 31, 2021
Jingfeng Zhang, Xilie Xu, Bo Han, Tongliang Liu, Gang Niu, Lizhen Cui, Masashi Sugiyama


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Estimating Instance-dependent Label-noise Transition Matrix using DNNs


May 27, 2021
Shuo Yang, Erkun Yang, Bo Han, Yang Liu, Min Xu, Gang Niu, Tongliang Liu


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Meta Discovery: Learning to Discover Novel Classes given Very Limited Data


Feb 18, 2021
Haoang Chi, Feng Liu, Wenjing Yang, Long Lan, Tongliang Liu, Gang Niu, Bo Han


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Guided Interpolation for Adversarial Training


Feb 15, 2021
Chen Chen, Jingfeng Zhang, Xilie Xu, Tianlei Hu, Gang Niu, Gang Chen, Masashi Sugiyama


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Learning from Similarity-Confidence Data


Feb 13, 2021
Yuzhou Cao, Lei Feng, Yitian Xu, Bo An, Gang Niu, Masashi Sugiyama

* 33 pages, 5 figures 

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CIFS: Improving Adversarial Robustness of CNNs via Channel-wise Importance-based Feature Selection


Feb 10, 2021
Hanshu Yan, Jingfeng Zhang, Gang Niu, Jiashi Feng, Vincent Y. F. Tan, Masashi Sugiyama


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Understanding the Interaction of Adversarial Training with Noisy Labels


Feb 09, 2021
Jianing Zhu, Jingfeng Zhang, Bo Han, Tongliang Liu, Gang Niu, Hongxia Yang, Mohan Kankanhalli, Masashi Sugiyama


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Learning Diverse-Structured Networks for Adversarial Robustness


Feb 08, 2021
Xuefeng Du, Jingfeng Zhang, Bo Han, Tongliang Liu, Yu Rong, Gang Niu, Junzhou Huang, Masashi Sugiyama

* 26 pages, 8 figures 

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Learning Noise Transition Matrix from Only Noisy Labels via Total Variation Regularization


Feb 04, 2021
Yivan Zhang, Gang Niu, Masashi Sugiyama


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Provably End-to-end Label-Noise Learning without Anchor Points


Feb 04, 2021
Xuefeng Li, Tongliang Liu, Bo Han, Gang Niu, Masashi Sugiyama


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Binary Classification from Multiple Unlabeled Datasets via Surrogate Set Classification


Feb 01, 2021
Shida Lei, Nan Lu, Gang Niu, Issei Sato, Masashi Sugiyama


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Tackling Instance-Dependent Label Noise via a Universal Probabilistic Model


Jan 14, 2021
Qizhou Wang, Bo Han, Tongliang Liu, Gang Niu, Jian Yang, Chen Gong


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SemiNLL: A Framework of Noisy-Label Learning by Semi-Supervised Learning


Dec 02, 2020
Zhuowei Wang, Jing Jiang, Bo Han, Lei Feng, Bo An, Gang Niu, Guodong Long


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A Survey of Label-noise Representation Learning: Past, Present and Future


Nov 09, 2020
Bo Han, Quanming Yao, Tongliang Liu, Gang Niu, Ivor W. Tsang, James T. Kwok, Masashi Sugiyama

* The draft is kept updating; any comments and suggestions are welcome 

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Maximum Mean Discrepancy is Aware of Adversarial Attacks


Oct 22, 2020
Ruize Gao, Feng Liu, Jingfeng Zhang, Bo Han, Tongliang Liu, Gang Niu, Masashi Sugiyama


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Pointwise Binary Classification with Pairwise Confidence Comparisons


Oct 05, 2020
Lei Feng, Senlin Shu, Nan Lu, Bo Han, Miao Xu, Gang Niu, Bo An, Masashi Sugiyama


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Geometry-aware Instance-reweighted Adversarial Training


Oct 05, 2020
Jingfeng Zhang, Jianing Zhu, Gang Niu, Bo Han, Masashi Sugiyama, Mohan Kankanhalli


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