| Make Landscape Flatter in Differentially Private Federated Learning Y Shi, Y Liu, K Wei, L Shen, X Wang, D Tao 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR …, 2023 | 46 | 2023 |
| Improving the Model Consistency of Decentralized Federated Learning Y Shi, L Shen, K Wei, Y Sun, B Yuan, X Wang, D Tao 2023 The Fortieth International Conference on Machine Learning (ICML), 31269 …, 2023 | 41 | 2023 |
| Efficient federated prompt tuning for black-box large pre-trained models Z Lin, Y Sun, Y Shi, X Wang, L Huang, L Shen, D Tao arXiv preprint arXiv:2310.03123, 2023 | 11 | 2023 |
| Towards more suitable personalization in federated learning via decentralized partial model training Y Shi, Y Liu, Y Sun, Z Lin, L Shen, X Wang, D Tao arXiv preprint arXiv:2305.15157, 2023 | 6 | 2023 |
| Efficient Federated Learning with Enhanced Privacy via Lottery Ticket Pruning in Edge Computing Y Shi, K Wei, L Shen, J Li, X Wang, B Yuan, S Guo 2024 IEEE Transactions on Mobile Computing (9946 - 9958), 2024 | 4 | 2024 |
| Towards the flatter landscape and better generalization in federated learning under client-level differential privacy Y Shi, K Wei, L Shen, Y Liu, X Wang, B Yuan, D Tao arXiv preprint arXiv:2305.00873, 2023 | 2 | 2023 |
| Decentralized Directed Collaboration for Personalized Federated Learning Y Liu, Y Shi, Q Li, B Wu, X Wang, L Shen 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024 | | 2024 |
| Enhancing Personal Decentralized Federated Learning through Model Decoupling Y Shi, Y Liu, Y Sun, Z Lin, L Shen, X Wang, D Tao | | |
xueqian wangTsinghua UniversityDirección de correo verificada de sz.tsinghua.edu.cn
