Bo Han

Cited by

	All	Since 2016
Citations	749	742
h-index	11	11
i10-index	15	15

500

250

125

375

20152016201720182019202020215 9 10 33 152 491 32

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
Tongliang LiuUniversity of Sydney and Visiting Scientist at RIKEN AIPVerified email at sydney.edu.au
Miao XuRIKEN, AIPVerified email at lamda.nju.edu.cn
Xingrui YuPh.D Student, University of Technology Sydney (UTS)Verified email at student.uts.edu.au
Nannan WangProfessor, Xidian UniversityVerified email at xidian.edu.cn
Jiangchao YaoAlibaba GroupVerified email at sjtu.edu.cn
Weihua HuPh.D. student, Stanford UniversityVerified email at stanford.edu
Mingming GongThe University of MelbourneVerified email at unimelb.edu.au
Jingfeng ZhangPhD, National University of SingaporeVerified email at comp.nus.edu.sg
Ling Chenuniversity of technology sydneyVerified email at uts.edu.au
Chen GongNanjing University of Science and TechnologyVerified email at sjtu.edu.cn
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
Lei Feng (冯磊)Chongqing UniversityVerified email at cqu.edu.cn
Mingyuan ZhouAssociate Professor, University of Texas at AustinVerified email at mccombs.utexas.edu
Feng LiuUniversity of Technology SydneyVerified email at ieee.org
laura wynterIBM Watson Research CenterVerified email at us.ibm.com

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	311	2018
How does Disagreement Help Generalization against Label Corruption? X Yu, B Han, J Yao, G Niu, IW Tsang, M Sugiyama ICML 2019, 2019	92*	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	75	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	41	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	22	2017
On the Convergence of a Family of Robust Losses for Stochastic Gradient Descent B Han, IW Tsang, L Chen ECML 2016, 2016	18	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	16	2019
Efficient Nonconvex Regularized Tensor Completion with Structure-aware Proximal Iterations Q Yao, JT Kwok, B Han ICML 2019, 2019	13*	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
Searching to Exploit Memorization Effect in Learning with Noisy Labels Q Yao, H Yang, B Han, G Niu, JT Kwok ICML 2020, 2020	12*	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	11	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	11	2020
Robust Plackett–Luce Model for k-ary Crowdsourced Preferences B Han, Y Pan, IW Tsang Machine Learning Journal, 2017	11	2017
Learning from Multiple Complementary Labels L Feng, T Kaneko, B Han, G Niu, B An, M Sugiyama ICML 2020, 2020	10	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	9	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	9	2019
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	9	2015
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
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	6	2020

The system can't perform the operation now. Try again later.

Articles 1–20

Citations per year

Duplicate citations

Merged citations

Add co-authorsCo-authors

Upload PDF

Follow this author

Cited by

Co-authors