| Fine-Grained Analysis of Stability and Generalization for Stochastic Gradient Descent Y Lei, Y Ying International Conference on Machine Learning, 5809-5819, 2020 | 140 | 2020 |
| 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 | 140 | 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 | 80 | 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 | 61 | 2015 |
| Sharper Generalization Bounds for Learning with Gradient-dominated Objective Functions Y Lei, Y Ying International Conference on Learning Representations, 2021 | 50 | 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 | 49 | 2021 |
| Sharper generalization bounds for pairwise learning Y Lei, A Ledent, M Kloft Advances in Neural Information Processing Systems 33, 21236-21246, 2020 | 46 | 2020 |
| 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 | 42 | 2015 |
| 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 | 35 | 2019 |
| Local rademacher complexity-based learning guarantees for multi-task learning N Yousefi, Y Lei, M Kloft, M Mollaghasemi, GC Anagnostopoulos Journal of Machine Learning Research 19 (38), 1-47, 2018 | 34 | 2018 |
| Simple stochastic and online gradient descent algorithms for pairwise learning Z Yang, Y Lei, P Wang, T Yang, Y Ying Advances in Neural Information Processing Systems 34, 20160-20171, 2021 | 32 | 2021 |
| 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 | 32 | 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 | 31 | 2022 |
| Generalization guarantee of SGD for pairwise learning Y Lei, M Liu, Y Ying Advances in neural information processing systems 34, 21216-21228, 2021 | 31 | 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 | 31 | 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 | 30* | 2021 |
| Stochastic Proximal AUC Maximization Y Lei, Y Ying Journal of Machine Learning Research 22 (61), 1-45, 2021 | 29 | 2021 |
| Boosted Kernel Ridge Regression: Optimal Learning Rates and Early Stopping SB Lin, Y Lei, DX Zhou Journal of Machine Learning Research 20 (46), 1-36, 2019 | 27 | 2019 |
| Stochastic composite mirror descent: Optimal bounds with high probabilities Y Lei, K Tang Advances in Neural Information Processing Systems 31, 1526-1536, 2018 | 26 | 2018 |
| Differentially private sgda for minimax problems Z Yang, S Hu, Y Lei, KR Vashney, S Lyu, Y Ying Uncertainty in Artificial Intelligence, 2192-2202, 2022 | 25 | 2022 |
Yiming YingSchool of Mathematics and Statistics, University of SydneyVerified email at sydney.edu.au
