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Relational Subsets Knowledge Distillation for Long-tailed Retinal Diseases Recognition


Apr 22, 2021
Lie Ju, Xin Wang, Lin Wang, Tongliang Liu, Xin Zhao, Tom Drummond, Dwarikanath Mahapatra, Zongyuan Ge


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Removing Adversarial Noise in Class Activation Feature Space


Apr 19, 2021
Dawei Zhou, Nannan Wang, Chunlei Peng, Xinbo Gao, Xiaoyu Wang, Jun Yu, Tongliang Liu


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Learning with Group Noise


Mar 17, 2021
Qizhou Wang, Jiangchao Yao, Chen Gong, Tongliang Liu, Mingming Gong, Hongxia Yang, Bo Han


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A Machine Learning Approach for Predicting Human Preference for Graph Layouts


Mar 01, 2021
Shijun Cai, Seok-Hee Hong, Jialiang Shen, Tongliang Liu

* 9 pages, 9 figures, PacificVis_Notes 

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Improving Medical Image Classification with Label Noise Using Dual-uncertainty Estimation


Feb 28, 2021
Lie Ju, Xin Wang, Lin Wang, Dwarikanath Mahapatra, Xin Zhao, Mehrtash Harandi, Tom Drummond, Tongliang Liu, Zongyuan Ge


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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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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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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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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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COVID-MTL: Multitask Learning with Shift3D and Random-weighted Loss for Automated Diagnosis and Severity Assessment of COVID-19


Dec 31, 2020
Guoqing Bao, Huai Chen, Tongliang Liu, Guanzhong Gong, Yong Yin, Lisheng Wang, Xiuying Wang

* COVID-19 research; computer vision and pattern recognition; 13 pages, 10 figures and 5 tables 

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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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Extended T: Learning with Mixed Closed-set and Open-set Noisy Labels


Dec 02, 2020
Xiaobo Xia, Tongliang Liu, Bo Han, Nannan Wang, Jiankang Deng, Jiatong Li, Yinian Mao


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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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Experimental Quantum Generative Adversarial Networks for Image Generation


Oct 21, 2020
He-Liang Huang, Yuxuan Du, Ming Gong, Youwei Zhao, Yulin Wu, Chaoyue Wang, Shaowei Li, Futian Liang, Jin Lin, Yu Xu, Rui Yang, Tongliang Liu, Min-Hsiu Hsieh, Hui Deng, Hao Rong, Cheng-Zhi Peng, Chao-Yang Lu, Yu-Ao Chen, Dacheng Tao, Xiaobo Zhu, Jian-Wei Pan

* Our first version was submitted to the journal in January 2020. Comments are welcome 

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Quantum differentially private sparse regression learning


Jul 23, 2020
Yuxuan Du, Min-Hsiu Hsieh, Tongliang Liu, Shan You, Dacheng Tao


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Weakly Supervised Temporal Action Localization with Segment-Level Labels


Jul 03, 2020
Xinpeng Ding, Nannan Wang, Xinbo Gao, Jie Li, Xiaoyu Wang, Tongliang Liu

* 18 pages,7 figures 

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Parts-dependent Label Noise: Towards Instance-dependent Label Noise


Jun 14, 2020
Xiaobo Xia, Tongliang Liu, Bo Han, Nannan Wang, Mingming Gong, Haifeng Liu, Gang Niu, Dacheng Tao, Masashi Sugiyama


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Class2Simi: A New Perspective on Learning with Label Noise


Jun 14, 2020
Songhua Wu, Xiaobo Xia, Tongliang Liu, Bo Han, Mingming Gong, Nannan Wang, Haifeng Liu, Gang Niu


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Dual T: Reducing Estimation Error for Transition Matrix in Label-noise Learning


Jun 14, 2020
Yu Yao, Tongliang Liu, Bo Han, Mingming Gong, Jiankang Deng, Gang Niu, Masashi Sugiyama


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Repulsive Mixture Models of Exponential Family PCA for Clustering


Apr 07, 2020
Maoying Qiao, Tongliang Liu, Jun Yu, Wei Bian, Dacheng Tao


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Quantum noise protects quantum classifiers against adversaries


Mar 20, 2020
Yuxuan Du, Min-Hsiu Hsieh, Tongliang Liu, Dacheng Tao, Nana Liu

* 16 pages, 8 figures 

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Multi-Class Classification from Noisy-Similarity-Labeled Data


Feb 16, 2020
Songhua Wu, Xiaobo Xia, Tongliang Liu, Bo Han, Mingming Gong, Nannan Wang, Haifeng Liu, Gang Niu


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Towards Mixture Proportion Estimation without Irreducibility


Feb 10, 2020
Yu Yao, Tongliang Liu, Bo Han, Mingming Gong, Gang Niu, Masashi Sugiyama, Dacheng Tao


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Confidence Scores Make Instance-dependent Label-noise Learning Possible


Jan 11, 2020
Antonin Berthon, Bo Han, Gang Niu, Tongliang Liu, Masashi Sugiyama


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A Shape Transformation-based Dataset Augmentation Framework for Pedestrian Detection


Dec 15, 2019
Zhe Chen, Wanli Ouyang, Tongliang Liu, Dacheng Tao


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