| Sample-level data selection for federated learning A Li, L Zhang, J Tan, Y Qin, J Wang, XY Li IEEE INFOCOM 2021-IEEE Conference on Computer Communications, 1-10, 2021 | 108 | 2021 |
| Privacy-preserving efficient federated-learning model debugging A Li, L Zhang, J Wang, F Han, XY Li IEEE Transactions on Parallel and Distributed Systems 33 (10), 2291-2303, 2021 | 47 | 2021 |
| Efficient federated-learning model debugging A Li, L Zhang, J Wang, J Tan, F Han, Y Qin, NM Freris, XY Li 2021 IEEE 37th International Conference on Data Engineering (ICDE), 372-383, 2021 | 37 | 2021 |
| Fedfaim: A model performance-based fair incentive mechanism for federated learning Z Shi, L Zhang, Z Yao, L Lyu, C Chen, L Wang, J Wang, XY Li IEEE Transactions on Big Data, 2022 | 33 | 2022 |
| Efficient participant contribution evaluation for horizontal and vertical federated learning J Wang, L Zhang, A Li, X You, H Cheng 2022 IEEE 38th International Conference on Data Engineering (ICDE), 911-923, 2022 | 25 | 2022 |
| Tight memory-regret lower bounds for streaming bandits S Li, L Zhang, J Wang, XY Li arXiv preprint arXiv:2306.07903, 2023 | 4 | 2023 |
| TVFL: Tunable Vertical Federated Learning towards Communication-Efficient Model Serving J Wang, L Zhang, Y Cheng, S Li, H Zhang, D Huang, X Lan IEEE INFOCOM 2023-IEEE Conference on Computer Communications, 1-10, 2023 | 3 | 2023 |
lan zhangUniversity of Science and Technology of China在 ustc.edu.cn 的电子邮件经过验证
