Tongliang Liu 个人学术档案

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	总计	2019 年至今
引用	15712	14399
h 指数	66	63
i10 指数	174	173

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Dacheng TaoNanyang Technological University在 ntu.edu.sg 的电子邮件经过验证
Bo HanHKBU / RIKEN在 comp.hkbu.edu.hk 的电子邮件经过验证
Mingming GongUniversity of Melbourne & Mohamed bin Zayed University of Artificial Intelligence在 unimelb.edu.au 的电子邮件经过验证
Gang NiuRIKEN Center for Advanced Intelligence Project在 riken.jp 的电子邮件经过验证
Xiaobo XiaPh.D. student, The University of Sydney在 uni.sydney.edu.au 的电子邮件经过验证
Masashi SugiyamaDirector, RIKEN Center for Advanced Intelligence Project / Professor, The University of Tokyo在 k.u-tokyo.ac.jp 的电子邮件经过验证
Chen GongProfessor@Nanjing University of Science and Technology在 njust.edu.cn 的电子邮件经过验证
Nannan WangProfessor, Xidian University在 xidian.edu.cn 的电子邮件经过验证
Kun ZhangCarnegie Mellon University & Mohamed bin Zayed University of Artificial Intelligence (MBZUAI)在 cmu.edu 的电子邮件经过验证
Yuxuan DuNanyang Technological University在 uni.sydney.edu.au 的电子邮件经过验证
Erkun Yang（杨二昆）Xidian University在 xidian.edu.cn 的电子邮件经过验证
Cheng Deng （邓成）School of Electronic Engineering, Xi'an 710071, Xidian University在 mail.xidian.edu.cn 的电子邮件经过验证
Li ShenSun Yat-sen University在 mail.sysu.edu.cn 的电子邮件经过验证
Yu YaoLecturer in the University of Sydney在 sydney.edu.au 的电子邮件经过验证
Jiankang DengImperial College London在 imperial.ac.uk 的电子邮件经过验证
Feng Liu (he/him)Lecturer, University of Melbourne / Visiting Scientist, RIKEN-AIP / Visiting Fellow, UTS-AAII在 unimelb.edu.au 的电子邮件经过验证
Yong LuoWuhan University在 whu.edu.cn 的电子邮件经过验证
Yang LiuComputer Science and Engineering, UC Santa Cruz在 ucsc.edu 的电子邮件经过验证
Yonggang ZHANGHKBU在 comp.hkbu.edu.hk 的电子邮件经过验证
Jingfeng ZhangLecturer@University of Auckland & Scientist@RIKEN AIP在 riken.jp 的电子邮件经过验证

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Tongliang Liu

Director, Sydney AI Centre, University of Sydney & Mohamed bin Zayed University of AI

在 sydney.edu.au 的电子邮件经过验证 - 首页

Machine Learning Learning with Noisy Labels Trustworthy Machine Learning


标题按引用次数排序按年份排序按标题排序	引用次数引用次数	年份
Classification with noisy labels by importance reweighting T Liu, D Tao IEEE Transactions on pattern analysis and machine intelligence 38 (3), 447-461, 2016	931	2016
Deep domain generalization via conditional invariant adversarial networks Y Li, X Tian, M Gong, Y Liu, T Liu, K Zhang, D Tao ECCV 2018, 624-639, 2018	724	2018
On compressing deep models by low rank and sparse decomposition X Yu, T Liu, X Wang, D Tao CVPR 2017, 7370-7379, 2017	481	2017
Multiple Kernel -Means with Incomplete Kernels X Liu, X Zhu, M Li, L Wang, E Zhu, T Liu, M Kloft, D Shen, J Yin, W Gao IEEE transactions on pattern analysis and machine intelligence 42 (5), 1191-1204, 2019	408	2019
Domain adaptation with conditional transferable components M Gong, K Zhang, T Liu, D Tao, C Glymour, B Schölkopf ICML 2016, 2839-2848, 2016	395	2016
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, 6835--6846, 2019	367	2019
dipIQ: Blind image quality assessment by learning-to-rank discriminable image pairs K Ma, W Liu, T Liu, Z Wang, D Tao IEEE Transactions on Image Processing 26 (8), 3951-3964, 2017	330	2017
Expressive power of parametrized quantum circuits Y Du, MH Hsieh, T Liu, D Tao Physical Review Research 2 (3), 033125, 2020	303	2020
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 33, 2020	271	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 2020, 2020	262	2020
Fast supervised discrete hashing J Gui, T Liu, Z Sun, D Tao, T Tan IEEE transactions on pattern analysis and machine intelligence 40 (2), 490-496, 2017	262	2017
Cris: Clip-driven referring image segmentation Z Wang, Y Lu, Q Li, X Tao, Y Guo, M Gong, T Liu CVPR 2022, 11686-11695, 2022	255	2022
Domain generalization via entropy regularization S Zhao, M Gong, T Liu, H Fu, D Tao NeurIPS 2020 33, 2020	231	2020
Sub-center ArcFace: Boosting Face Recognition by Large-scale Noisy Web Faces J Deng, J Guo, T Liu, M Gong, S Zafeiriou ECCV 2020, 2020	224	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 33, 2020	222	2020
Why resnet works? residuals generalize F He, T Liu, D Tao IEEE transactions on neural networks and learning systems, 2019	214	2019
Domain generalization via conditional invariant representation Y Li, M Gong, X Tian, T Liu, D Tao AAAI 2018, 2018	214	2018
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	208	2022
Control batch size and learning rate to generalize well: Theoretical and empirical evidence F He, T Liu, D Tao NeurIPS 2019 32, 1143-1152, 2019	204	2019
Learning with biased complementary labels X Yu, T Liu, M Gong, D Tao ECCV 2018, 68-83, 2018	204	2018

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