Gang Niu

Cited by

	All	Since 2016
Citations	3787	3598
h-index	29	29
i10-index	50	48

1700

850

425

1275

201220132014201520162017201820192020202115 36 49 53 92 117 228 437 1072 1605

Public access

View all

22 articles

0 articles

available

not available

Based on funding mandates

Co-authors

Masashi SugiyamaDirector, RIKEN Center for Advanced Intelligence Project / Professor, The University of TokyoVerified email at k.u-tokyo.ac.jp
Bo HanHKBU / RIKENVerified email at comp.hkbu.edu.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
Ivor W. TsangResearch Director & Professor, Australian AI Institute, University of Technology SydneyVerified email at uts.edu.au
Quanming YaoAssistant Professor, EE Department, Tsinghua UniversityVerified email at tsinghua.edu.cn
Tomoya SakaiNEC CorporationVerified email at nec.com
Xingrui YuPh.D Student, University of Technology Sydney (UTS)Verified email at student.uts.edu.au
Weihua HuPh.D. student, Stanford UniversityVerified email at stanford.edu
Mingming GongThe University of MelbourneVerified email at unimelb.edu.au
Bo DaiResearch Scientist, Google BrainVerified email at google.com
Jingfeng ZhangPhD, NUS, Singapore ---> Postdoc, RIKEN-AIP, TokyoVerified email at riken.jp
Xiaobo XiaPh.D. student, The University of SydneyVerified email at uni.sydney.edu.au
Makoto YamadaKyoto University / RIKEN Center for Advanced Intelligence Project (AIP)Verified email at i.kyoto-u.ac.jp
Jiangchao YaoAlibaba GroupVerified email at sjtu.edu.cn
Lei FengChongqing University / RIKEN Center for Advanced Intelligence ProjectVerified email at cqu.edu.cn
Takashi IshidaLecturer, The University of TokyoVerified email at ms.k.u-tokyo.ac.jp
Bo AnNanyang Technological UniversityVerified email at ntu.edu.sg
Nannan WangProfessor, Xidian UniversityVerified email at xidian.edu.cn
Chen GongProfessor@Nanjing University of Science and TechnologyVerified email at sjtu.edu.cn

Gang Niu

RIKEN Center for Advanced Intelligence Project

Verified email at postman.riken.jp - 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	678	2018
Positive-unlabeled learning with non-negative risk estimator R Kiryo, G Niu, MC Plessis, M Sugiyama NeurIPS 2017 (oral), 2017	241	2017
Analysis of learning from positive and unlabeled data MC du Plessis, G Niu, M Sugiyama NeurIPS 2014, 2014	236	2014
How does disagreement help generalization against label corruption? X Yu, B Han, J Yao, G Niu, IW Tsang, M Sugiyama ICML 2019, 2019	225	2019
Convex formulation for learning from positive and unlabeled data MC du Plessis, G Niu, M Sugiyama ICML 2015, 2015	204	2015
Class-prior estimation for learning from positive and unlabeled data MC du Plessis, G Niu, M Sugiyama Machine Learning 106 (4), 463--492, 2017	168*	2017
Analysis and improvement of policy gradient estimation T Zhao, H Hachiya, G Niu, M Sugiyama NeurIPS 2011, 2011	134	2011
Masking: A new perspective of noisy supervision B Han, J Yao, G Niu, M Zhou, IW Tsang, Y Zhang, M Sugiyama NeurIPS 2018, 2018	119	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	106	2019
Does distributionally robust supervised learning give robust classifiers? W Hu, G Niu, I Sato, M Sugiyama ICML 2018, 2018	104	2018
Semi-supervised classification based on classification from positive and unlabeled data T Sakai, MC du Plessis, G Niu, M Sugiyama ICML 2017, 2017	92	2017
Information-theoretic semi-supervised metric learning via entropy regularization G Niu, B Dai, M Yamada, M Sugiyama ICML 2012, 2012	92	2012
Theoretical comparisons of positive-unlabeled learning against positive-negative learning G Niu, MC du Plessis, T Sakai, Y Ma, M Sugiyama NeurIPS 2016, 2016	89	2016
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	76	2020
Information-maximization clustering based on squared-loss mutual information M Sugiyama, G Niu, M Yamada, M Kimura, H Hachiya Neural Computation 26 (1), 84--131, 2014	74*	2014
Learning from complementary labels T Ishida, G Niu, W Hu, M Sugiyama NeurIPS 2017, 2017	70	2017
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	60*	2020
Squared-loss mutual information regularization: A novel information-theoretic approach to semi-supervised learning G Niu, W Jitkrittum, B Dai, H Hachiya, M Sugiyama ICML 2013, 2013	58	2013
On the minimal supervision for training any binary classifier from only unlabeled data N Lu, G Niu, AK Menon, M Sugiyama ICLR 2019, 2019	54	2019
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 (spotlight), 2020	50	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

Follow this author

Cited by

Co-authors