Bo Han

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Gang NiuRIKEN Center for Advanced Intelligence ProjectVerified email at postman.riken.jp
Masashi SugiyamaDirector, RIKEN Center for Advanced Intelligence Project / Professor, The University of TokyoVerified email at k.u-tokyo.ac.jp
Tongliang LiuDirector, Sydney AI Centre, University of SydneyVerified email at sydney.edu.au
Ivor W. Tsang, IEEE FellowInaugural A*STAR AI Fellow and Director, Centre for Frontier AI Research, A*STARVerified email at ihpc.a-star.edu.sg
Quanming YaoAssistant Professor, EE Department, Tsinghua UniversityVerified email at tsinghua.edu.cn
Miao XuUniversity of Queensland, RIKEN AIPVerified email at uq.edu.au
Xingrui YuPh.D Student, University of Technology Sydney (UTS)Verified email at student.uts.edu.au
Jiangchao YaoShanghai Jiao Tong UniversityVerified email at sjtu.edu.cn
Nannan WangProfessor, Xidian UniversityVerified email at xidian.edu.cn
Mingming GongUniversity of MelbourneVerified email at unimelb.edu.au
Chen GongProfessor@Nanjing University of Science and TechnologyVerified email at njust.edu.cn
Xiaobo XiaPh.D. student, The University of SydneyVerified email at uni.sydney.edu.au
Jingfeng ZhangPhD, NUS, Singapore ---> Postdoc, RIKEN-AIP, TokyoVerified email at riken.jp
Weihua HuPh.D. student, Stanford UniversityVerified email at stanford.edu
Mohan KankanhalliProfessor of Computer Science, National University of SingaporeVerified email at comp.nus.edu.sg
Mingyuan ZhouAssociate Professor, University of Texas at AustinVerified email at mccombs.utexas.edu
James T. KwokProfessor of Computer Science and Engineering, Hong Kong University of Science and TechnologyVerified email at cse.ust.hk
Lei FengChongqing University / RIKEN Center for Advanced Intelligence ProjectVerified email at cqu.edu.cn
Feng Liu (刘峰)Lecturer, DeSI Lab, AAII, University of Technology SydneyVerified email at ieee.org
Ling Chenuniversity of technology sydneyVerified email at uts.edu.au

Bo Han

HKBU / RIKEN

Verified email at comp.hkbu.edu.hk - Homepage

Machine Learning


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Co-teaching: Robust Training of Deep Neural Networks with Extremely Noisy Labels B Han, Q Yao, X Yu, G Niu, M Xu, W Hu, IW Tsang, M Sugiyama NeurIPS 2018, 2018	866	2018
How does Disagreement Help Generalization against Label Corruption? X Yu, B Han, J Yao, G Niu, IW Tsang, M Sugiyama ICML 2019, 2019	295	2019
Masking: A New Perspective of Noisy Supervision B Han, J Yao, G Niu, M Zhou, IW Tsang, Y Zhang, M Sugiyama NeurIPS 2018, 2018	143	2018
Are Anchor Points Really Indispensable in Label-Noise Learning? X Xia, T Liu, N Wang, B Han, C Gong, G Niu, M Sugiyama NeurIPS 2019, 2019	134	2019
Attacks Which Do Not Kill Training Make Adversarial Learning Stronger J Zhang, X Xu, B Han, G Niu, L Cui, M Sugiyama, M Kankanhalli ICML 2020, 2020	128	2020
Geometry-aware Instance-reweighted Adversarial Training J Zhang, J Zhu, G Niu, B Han, M Sugiyama, M Kankanhalli ICLR 2021, 2021	81	2021
Part-dependent Label Noise: Towards Instance-dependent Label Noise X Xia, T Liu, B Han, N Wang, M Gong, H Liu, G Niu, D Tao, M Sugiyama NeurIPS 2020, 2020	72	2020
SIGUA: Forgetting May Make Learning with Noisy Labels More Robust B Han, G Niu, X Yu, Q Yao, M Xu, IW Tsang, M Sugiyama ICML 2020, 2020	71*	2020
Dual T: Reducing Estimation Error for Transition Matrix in Label-noise Learning Y Yao, T Liu, B Han, M Gong, J Deng, G Niu, M Sugiyama NeurIPS 2020, 2020	69	2020
Searching to Exploit Memorization Effect in Learning with Noisy Labels Q Yao, H Yang, B Han, G Niu, JT Kwok ICML 2020, 2020	49*	2020
Robust Early-learning: Hindering the Memorization of Noisy Labels X Xia, T Liu, B Han, C Gong, N Wang, Z Ge, Y Chang ICLR 2021, 2021	42	2021
Confidence Scores Make Instance-dependent Label-noise Learning Possible A Berthon, B Han, G Niu, T Liu, M Sugiyama ICML 2021, 2021	35	2021
Learning with Multiple Complementary Labels L Feng, T Kaneko, B Han, G Niu, B An, M Sugiyama ICML 2020, 2020	34	2020
A Survey of Label-noise Representation Learning: Past, Present and Future B Han, Q Yao, T Liu, G Niu, IW Tsang, JT Kwok, M Sugiyama arXiv preprint arXiv:2011.04406, 2020	34	2020
Towards Robust ResNet: A Small Step but A Giant Leap J Zhang, B Han, L Wynter, KH Low, M Kankanhalli IJCAI 2019, 2019	27	2019
Progressive Stochastic Learning for Noisy Labels B Han, IW Tsang, L Chen, C Yu, SF Fung IEEE Transactions on Neural Networks and Learning Systems, 2017	26	2017
Maximum Mean Discrepancy Test is Aware of Adversarial Attacks R Gao, F Liu, J Zhang, B Han, T Liu, G Niu, M Sugiyama ICML 2021, 2021	24*	2021
Class2simi: A Noise Reduction Perspective on Learning with Noisy Labels S Wu, X Xia, T Liu, B Han, M Gong, N Wang, H Liu, G Niu ICML 2021, 2021	24*	2021
Provably Consistent Partial-Label Learning L Feng, J Lv, B Han, M Xu, G Niu, X Geng, B An, M Sugiyama NeurIPS 2020, 2020	24	2020
Butterfly: One-step Approach towards Wildly Unsupervised Domain Adaptation F Liu, J Lu, B Han, G Niu, G Zhang, M Sugiyama NeurIPS 2019 workshop, 2019	24*	2019

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