Gang Niu

Получаване на мой собствен потребителски профил

Позовавания

	Всички	От 2019
Позовавания	13195	12555
h-индекс	53	50
i10-индекс	100	96

3500

1750

875

2625

2014201520162017201820192020202120222023202444 55 80 110 227 410 1063 1889 2513 3120 3465

Публичен достъп

Преглед на всички

59 статии

0 статии*

налични

неналични

Въз основа на изисквания при финансирането

Съавтори

Masashi SugiyamaDirector, RIKEN Center for Advanced Intelligence Project / Professor, The University of TokyoПотвърден имейл адрес: k.u-tokyo.ac.jp
Bo HanHKBU / RIKENПотвърден имейл адрес: comp.hkbu.edu.hk
Tongliang LiuDirector, Sydney AI Centre, University of Sydney & Mohamed bin Zayed University of AIПотвърден имейл адрес: sydney.edu.au
Miao XuUniversity of Queensland, RIKEN AIPПотвърден имейл адрес: uq.edu.au
Ivor W. Tsang, IEEE FellowInaugural A*STAR AI Fellow and Director, Centre for Frontier AI Research, A*STARПотвърден имейл адрес: cfar.a-star.edu.sg
Lei FengSingapore University of Technology and DesignПотвърден имейл адрес: sutd.edu.sg
Jingfeng ZhangLecturer@University of Auckland & Scientist@RIKEN AIPПотвърден имейл адрес: riken.jp
Quanming YaoAssistant Professor, EE Department, Tsinghua UniversityПотвърден имейл адрес: tsinghua.edu.cn
Mingming GongUniversity of Melbourne & Mohamed bin Zayed University of Artificial IntelligenceПотвърден имейл адрес: unimelb.edu.au
Xingrui YuScientist, Centre for Frontier AI Research (CFAR), A*STARПотвърден имейл адрес: cfar.a-star.edu.sg
Weihua HuStanfordПотвърден имейл адрес: stanford.edu
Chen GongProfessor@Nanjing University of Science and TechnologyПотвърден имейл адрес: njust.edu.cn
Jiangchao YaoShanghai Jiao Tong UniversityПотвърден имейл адрес: sjtu.edu.cn
Bo AnNanyang Technological UniversityПотвърден имейл адрес: ntu.edu.sg
Tomoya SakaiIBM Research - TokyoПотвърден имейл адрес: ibm.com
Xiaobo XiaPostdoc, National University of SingaporeПотвърден имейл адрес: nus.edu.sg
Takashi IshidaResearch Scientist, RIKEN AIP / Lecturer, University of TokyoПотвърден имейл адрес: ms.k.u-tokyo.ac.jp
Nan LuUniversity of TübingenПотвърден имейл адрес: uni-tuebingen.de
Nannan WangProfessor, Xidian UniversityПотвърден имейл адрес: xidian.edu.cn
Yang LiuComputer Science and Engineering, UC Santa CruzПотвърден имейл адрес: ucsc.edu

Следене

Gang Niu

Други имена牛罡

Senior Research Scientist, RIKEN Center for Advanced Intelligence Project

Потвърден имейл адрес: riken.jp - Начална страница

Machine Learning


Заглавие Сортиране по цитати Сортиране по година Сортиране по заглавие	Позовавания Позовавания	Година
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	2357	2018
How does disagreement help generalization against label corruption? X Yu, B Han, J Yao, G Niu, IW Tsang, M Sugiyama ICML 2019, 2019	901	2019
Positive-unlabeled learning with non-negative risk estimator R Kiryo, G Niu, MC Plessis, M Sugiyama NeurIPS 2017 (oral), 2017	559	2017
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	470	2020
Analysis of learning from positive and unlabeled data MC du Plessis, G Niu, M Sugiyama NeurIPS 2014, 2014	455	2014
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	404	2019
Convex formulation for learning from positive and unlabeled data MC du Plessis, G Niu, M Sugiyama ICML 2015, 2015	386	2015
Does distributionally robust supervised learning give robust classifiers? W Hu, G Niu, I Sato, M Sugiyama ICML 2018, 2018	321	2018
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	317	2020
Geometry-aware instance-reweighted adversarial training J Zhang, J Zhu, G Niu, B Han, M Sugiyama, M Kankanhalli ICLR 2021 (oral), 2021	307	2021
Masking: A new perspective of noisy supervision B Han, J Yao, G Niu, M Zhou, IW Tsang, Y Zhang, M Sugiyama NeurIPS 2018, 2018	286	2018
Class-prior estimation for learning from positive and unlabeled data MC du Plessis, G Niu, M Sugiyama Machine Learning 106 (4), 463--492, 2017	263*	2017
Learning with noisy labels revisited: A study using real-world human annotations J Wei, Z Zhu, H Cheng, T Liu, G Niu, Y Liu ICLR 2022, 2022	261	2022
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	256	2020
Understanding and improving early stopping for learning with noisy labels Y Bai, E Yang, B Han, Y Yang, J Li, Y Mao, G Niu, T Liu NeurIPS 2021, 2021	223	2021
Progressive identification of true labels for partial-label learning J Lv, M Xu, L Feng, G Niu, X Geng, M Sugiyama ICML 2020, 2020	197	2020
Learning from complementary labels T Ishida, G Niu, W Hu, M Sugiyama NeurIPS 2017, 2017	192	2017
Analysis and improvement of policy gradient estimation T Zhao, H Hachiya, G Niu, M Sugiyama NeurIPS 2011, 2011	190	2011
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	182	2020
Provably consistent partial-label learning L Feng, J Lv, B Han, M Xu, G Niu, X Geng, B An, M Sugiyama NeurIPS 2020, 2020	164	2020

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