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To Aggregate or Not? Learning with Separate Noisy Labels


Jun 14, 2022
Jiaheng Wei, Zhaowei Zhu, Tianyi Luo, Ehsan Amid, Abhishek Kumar, Yang Liu

* Paper under Review 

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Beyond Images: Label Noise Transition Matrix Estimation for Tasks with Lower-Quality Features


Feb 02, 2022
Zhaowei Zhu, Jialu Wang, Yang Liu


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Learning with Noisy Labels Revisited: A Study Using Real-World Human Annotations


Oct 22, 2021
Jiaheng Wei, Zhaowei Zhu, Hao Cheng, Tongliang Liu, Gang Niu, Yang Liu


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Demystifying How Self-Supervised Features Improve Training from Noisy Labels


Oct 18, 2021
Hao Cheng, Zhaowei Zhu, Xing Sun, Yang Liu


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A Good Representation Detects Noisy Labels


Oct 12, 2021
Zhaowei Zhu, Zihao Dong, Hao Cheng, Yang Liu


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The Rich Get Richer: Disparate Impact of Semi-Supervised Learning


Oct 12, 2021
Zhaowei Zhu, Tianyi Luo, Yang Liu


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Clusterability as an Alternative to Anchor Points When Learning with Noisy Labels


Feb 10, 2021
Zhaowei Zhu, Yiwen Song, Yang Liu


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Identification of 27 abnormalities from multi-lead ECG signals: An ensembled Se-ResNet framework with Sign Loss function


Jan 12, 2021
Zhaowei Zhu, Xiang Lan, Tingting Zhao, Yangming Guo, Pipin Kojodjojo, Zhuoyang Xu, Zhuo Liu, Siqi Liu, Han Wang, Xingzhi Sun, Mengling Feng


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A Second-Order Approach to Learning with Instance-Dependent Label Noise


Dec 22, 2020
Zhaowei Zhu, Tongliang Liu, Yang Liu

* Learning with label noise 

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Federated Bandit: A Gossiping Approach


Oct 24, 2020
Zhaowei Zhu, Jingxuan Zhu, Ji Liu, Yang Liu

* 31 pages, 1 figure 

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