| DLB: a dynamic load balance strategy for distributed training of deep neural networks Q Ye, Y Zhou, M Shi, Y Sun, J Lv IEEE Transactions on Emerging Topics in Computational Intelligence, 2022 | 15* | 2022 |
| PRIOR: Personalized Prior for Reactivating the Information Overlooked in Federated Learning M Shi, Y Zhou, K Wang, H Zhang, S Huang, Q Ye, J Lv NeurIPS 2023, 2023 | 6* | 2023 |
| FLSGD: free local SGD with parallel synchronization Q Ye, Y Zhou, M Shi, J Lv The Journal of Supercomputing 78 (10), 12410-12433, 2022 | 5 | 2022 |
| Communication-efficient Federated Learning with Single-Step Synthetic Features Compressor for Faster Convergence Y Zhou, M Shi, Y Li, Y Sun, Q Ye, J Lv ICCV 2023, 5031-5040, 2023 | 4 | 2023 |
| DeFTA: A Plug-and-Play Peer-to-Peer Decentralized Federated Learning Framework Y Zhou, M Shi, Y Tian, Q Ye, J Lv Information Sciences, 2024 | 3* | 2024 |
| A Closer Look at Time Steps is Worthy of Triple Speed-Up for Diffusion Model Training K Wang*, Y Zhou*, M Shi*, Z Yuan, Y Shang, X Peng, H Zhang, Y You arXiv preprint arXiv:2405.17403, 2024 | | 2024 |
| Federated cINN Clustering for Accurate Clustered Federated Learning JL Yuhao Zhou, Minjia Shi, Yuxin Tian, Yuanxi Li, Qing Ye ICASSP2024, 2023 | | 2023 |
| Unconstrained Feature Model and Its General Geometric Patterns in Federated Learning: Local Subspace Minority Collapse M Shi, Y Zhou, Q Ye, J Lv ICONIP, 449-464, 2023 | | 2023 |
Yuhao ZhouSichuan UniversityVerified email at stu.scu.edu.cn
