Yunwen Lei

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Yiming YingProfessor, Department of Mathematics and Statistics, University at Albany, SUNYVerified email at albany.edu
Marius KloftTU KaiserslauternVerified email at cs.uni-kl.de
Ding-Xuan ZhouUniversity of SydneyVerified email at sydney.edu.au
Ke TangProfessor, Southern University of Science and TechnologyVerified email at sustech.edu.cn
Urun DoganResearch Scientist, MetaVerified email at fb.com
Antoine LedentSchool of Computing and Information Sciences (SCIS), Singapore Management University (SMU)Verified email at smu.edu.sg
Zhenhuan YangEtsyVerified email at etsy.com
Puyu WangCity University of Hong KongVerified email at cityu.edu.hk
Alexander BinderAssociate Professor, Singapore Institute of Technology (SIT) and University of Oslo (UiO)Verified email at singaporetech.edu.sg
Tianbao YangTexas A&M UniversityVerified email at tamu.edu
Waleed MustafaTU KaiserslauternVerified email at rhrk.uni-kl.de
Guiying LiSouthern University of Science and TechnologyVerified email at sustech.edu.cn
Siwei Lyu (吕思伟)Professor of CSE, University at Buffalo, SUNYVerified email at buffalo.edu
Shao-Bo LinSchool of Management, Xi'an Jiaotong UniversityVerified email at xjtu.edu.cn
Mingrui LiuGeorge Mason UniversityVerified email at gmu.edu
Clayton ScottProfessor of Electrical Engineering and Computer Science, University of MichiganVerified email at umich.edu
Srinagesh SharmaMicrosoftVerified email at microsoft.com
Junhong LinZhejiang UniversityVerified email at zju.edu.cn
Niloofar YousefiPostdoctoral Research AssociateVerified email at ucf.edu
Georgios C. AnagnostopoulosAssociate Professor, Florida Institute of TechnologyVerified email at fit.edu

Yunwen Lei

Hong Kong Baptist University

Verified email at hkbu.edu.hk - Homepage

Statistical Learning Theory Stochastic Optimization


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Stochastic gradient descent for nonconvex learning without bounded gradient assumptions Y Lei, T Hu, G Li, K Tang IEEE Transactions on Neural Networks and Learning Systems 31 (10), 4394-4400, 2020	89	2020
Fine-Grained Analysis of Stability and Generalization for Stochastic Gradient Descent Y Lei, Y Ying International Conference on Machine Learning, 5809-5819, 2020	83	2020
Data-dependent generalization bounds for multi-class classification Y Lei, Ü Dogan, DX Zhou, M Kloft IEEE Transactions on Information Theory 65 (5), 2995-3021, 2019	57	2019
Multi-class svms: From tighter data-dependent generalization bounds to novel algorithms Y Lei, Ü Dogan, A Binder, M Kloft Advances in Neural Information Processing Systems, 2026-2034, 2015	55	2015
Generalization performance of radial basis function networks Y Lei, L Ding, W Zhang IEEE Transactions on Neural Networks and Learning Systems 26 (3), 551-564, 2015	34	2015
Sharper Generalization Bounds for Learning with Gradient-dominated Objective Functions Y Lei, Y Ying International Conference on Learning Representations, 2021	25	2021
A generalization error bound for multi-class domain generalization AA Deshmukh, Y Lei, S Sharma, U Dogan, JW Cutler, C Scott arXiv preprint arXiv:1905.10392, 2019	25	2019
Localized Multiple Kernel Learning—A Convex Approach Y Lei, A Binder, U Dogan, M Kloft Proceedings of The 8th Asian Conference on Machine Learning 63, 81-96, 2016	25*	2016
Sharper Generalization Bounds for Pairwise Learning Y Lei, A Ledent, M Kloft Advances in Neural Information Processing Systems, 21236-21246, 2020	24	2020
Generalization Performance of Multi-pass Stochastic Gradient Descent with Convex Loss Functions Y Lei, T Hu, K Tang Journal of Machine Learning Research 22 (25), 1−41, 2021	23	2021
Stability and Generalization of Stochastic Gradient Methods for Minimax Problems Y Lei, Z Yang, T Yang, Y Ying International Conference on Machine Learning, 6175-6186, 2021	21	2021
Learning rates for stochastic gradient descent with nonconvex objectives Y Lei, K Tang IEEE Transactions on Pattern Analysis and Machine Intelligence 43 (12), 4505 …, 2021	21	2021
Norm-based generalisation bounds for deep multi-class convolutional neural networks A Ledent, W Mustafa, Y Lei, M Kloft Proceedings of the AAAI Conference on Artificial Intelligence 35 (9), 8279-8287, 2021	20*	2021
Differentially private SGD with non-smooth losses P Wang, Y Lei, Y Ying, H Zhang Applied and Computational Harmonic Analysis 56, 306-336, 2022	19	2022
Online pairwise learning algorithms with convex loss functions J Lin, Y Lei, B Zhang, DX Zhou Information Sciences 406, 57-70, 2017	19	2017
Local rademacher complexity bounds based on covering numbers Y Lei, L Ding, Y Bi Neurocomputing 218, 320-330, 2016	19	2016
Stability and differential privacy of stochastic gradient descent for pairwise learning with non-smooth loss Z Yang, Y Lei, S Lyu, Y Ying International Conference on Artificial Intelligence and Statistics, 2026-2034, 2021	18	2021
Convergence of online mirror descent Y Lei, DX Zhou Applied and Computational Harmonic Analysis 48 (1), 343-373, 2020	18*	2020
Stochastic Proximal AUC Maximization Y Lei, Y Ying Journal of Machine Learning Research 22 (61), 1-45, 2021	17	2021
Convergence of unregularized online learning algorithms Y Lei, L Shi, ZC Guo The Journal of Machine Learning Research 18 (1), 6269-6301, 2018	17	2018

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