Bo Han

Cited by

	All	Since 2015
Citations	623	622
h-index	10	10
i10-index	11	11

420

210

105

315

2015201620172018201920205 9 12 32 148 416

Co-authors

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
Ivor W. TsangResearch Director & Professor, Australian AI Institute, University of Technology SydneyVerified email at uts.edu.au
Quanming YaoSenior Scientist, 4ParadigmVerified email at cse.ust.hk
Xingrui YuPh.D Student, University of Technology Sydney (UTS)Verified email at student.uts.edu.au
Miao XuRIKEN, AIPVerified email at lamda.nju.edu.cn
Tongliang LiuUniversity of Sydney and Visiting Scientist at RIKEN AIPVerified email at sydney.edu.au
Jiangchao YaoAlibaba GroupVerified email at sjtu.edu.cn
Nannan WangProfessor, Xidian UniversityVerified email at xidian.edu.cn
Weihua HuPh.D. student, Stanford UniversityVerified email at stanford.edu
Jingfeng ZhangNational University of SingaporeVerified email at comp.nus.edu.sg
Mingming GongThe University of MelbourneVerified email at unimelb.edu.au
James T. KwokProfessor of Computer Science and Engineering, Hong Kong University of Science and TechnologyVerified email at cse.ust.hk
Mohan KankanhalliProfessor of Computer Science, National University of SingaporeVerified email at comp.nus.edu.sg
Chen GongNanjing University of Science and TechnologyVerified email at sjtu.edu.cn
Mingyuan ZhouAssociate Professor, University of Texas at AustinVerified email at mccombs.utexas.edu
Lei Feng (冯磊)Nanyang Technological UniversityVerified email at e.ntu.edu.sg
Feng LiuUniversity of Technology SydneyVerified email at ieee.org
laura wynterIBM Watson Research CenterVerified email at us.ibm.com
Zhi-Hua ZhouNanjing UniversityVerified email at nju.edu.cn

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	281	2018
How does Disagreement Help Generalization against Label Corruption? X Yu, B Han, J Yao, G Niu, IW Tsang, M Sugiyama ICML 2019, 2019	72*	2019
Masking: A New Perspective of Noisy Supervision B Han, J Yao, G Niu, M Zhou, IW Tsang, Z Ya, M Sugiyama NeurIPS 2018, 2018	63	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	29	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	18	2017
On the Convergence of a Family of Robust Losses for Stochastic Gradient Descent B Han, IW Tsang, L Chen ECML 2016, 2016	17	2016
Fast Image Recognition based on Independent Component Analysis S Zhang, B He, R Nian, J Wang, B Han, A Lendasse, G Yuan Cognitive Computation, 2014	17	2014
Towards Robust ResNet: A Small Step but A Giant Leap J Zhang, B Han, L Wynter, KH Low, M Kankanhalli IJCAI 2019, 2019	15	2019
Efficient Nonconvex Regularized Tensor Completion with Structure-aware Proximal Iterations Q Yao, JT Kwok, B Han ICML 2019, 2019	15*	2019
LARSEN: Selective Ensemble Learning using LARS for Blended Data B Han, B He, R Nian, M Ma, S Zhang, M Li, A Lendasse Neurocomputing, 2015	13*	2015
Robust Plackett–Luce Model for k-ary Crowdsourced Preferences B Han, Y Pan, IW Tsang Machine Learning Journal, 2017	10	2017
HSR: L 1/2-regularized Sparse Representation for Fast Face Recognition using Hierarchical Feature Selection B Han, B He, T Sun, T Yan, M Ma, Y Shen, A Lendasse Neural Computing and Applications, 2015	8	2015
Learning from Multiple Complementary Labels L Feng, T Kaneko, B Han, G Niu, B An, M Sugiyama ICML 2020, 2020	7	2020
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	7	2020
Butterfly: A Panacea for All Difficulties in Wildly Unsupervised Domain Adaptation F Liu, J Lu, B Han, G Niu, G Zhang, M Sugiyama arXiv preprint arXiv:1905.07720 presented at NeurIPS19 workshop, 2019	7	2019
Matrix co-completion for multi-label classification with missing features and labels M Xu, G Niu, B Han, IW Tsang, ZH Zhou, M Sugiyama arXiv preprint arXiv:1805.09156, 2018	7	2018
Searching to Exploit Memorization Effect in Learning with Noisy Labels Q Yao, H Yang, B Han, G Niu, JT Kwok ICML 2020, 2020	6*	2020
Confidence Scores Make Instance-dependent Label-noise Learning Possible A Berthon, B Han, G Niu, T Liu, M Sugiyama arXiv preprint arXiv:2001.03772, 2020	5	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	4	2020
Stagewise Learning for Noisy k-ary Preferences Y Pan, B Han, IW Tsang Machine Learning Journal, 2017	4	2017

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