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Yunwen Lei
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Cited by
Cited by
Year
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
1102020
Fine-Grained Analysis of Stability and Generalization for Stochastic Gradient Descent
Y Lei, Y Ying
International Conference on Machine Learning, 5809-5819, 2020
1032020
Data-dependent generalization bounds for multi-class classification
Y Lei, Dogan, DX Zhou, M Kloft
IEEE Transactions on Information Theory 65 (5), 2995-3021, 2019
652019
Multi-class svms: From tighter data-dependent generalization bounds to novel algorithms
Y Lei, Dogan, A Binder, M Kloft
Advances in Neural Information Processing Systems, 2026-2034, 2015
582015
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
382015
Sharper Generalization Bounds for Learning with Gradient-dominated Objective Functions
Y Lei, Y Ying
International Conference on Learning Representations, 2021
362021
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
322021
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
322019
Sharper Generalization Bounds for Pairwise Learning
Y Lei, A Ledent, M Kloft
Advances in Neural Information Processing Systems, 21236-21246, 2020
312020
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
282021
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
26*2016
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
25*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
242021
Stochastic Proximal AUC Maximization
Y Lei, Y Ying
Journal of Machine Learning Research 22 (61), 1-45, 2021
232021
Differentially private SGD with non-smooth losses
P Wang, Y Lei, Y Ying, H Zhang
Applied and Computational Harmonic Analysis 56, 306-336, 2022
222022
Local rademacher complexity-based learning guarantees for multi-task learning
N Yousefi, Y Lei, M Kloft, M Mollaghasemi, GC Anagnostopoulos
The Journal of Machine Learning Research 19 (1), 1385-1431, 2018
222018
Convergence of online mirror descent
Y Lei, DX Zhou
Applied and Computational Harmonic Analysis 48 (1), 343-373, 2020
212020
Online pairwise learning algorithms with convex loss functions
J Lin, Y Lei, B Zhang, DX Zhou
Information Sciences 406, 57-70, 2017
212017
Local rademacher complexity bounds based on covering numbers
Y Lei, L Ding, Y Bi
Neurocomputing 218, 320-330, 2016
212016
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
202021
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