| Communication-efficient federated learning with adaptive quantization Y Mao, Z Zhao, G Yan, Y Liu, T Lan, L Song, W Ding ACM Transactions on Intelligent Systems and Technology (TIST) 13 (4), 1-26, 2022 | 43 | 2022 |
| Towards efficient communications in federated learning: A contemporary survey Z Zhao, Y Mao, Y Liu, L Song, Y Ouyang, X Chen, W Ding Journal of the Franklin Institute 360 (12), 8669-8703, 2023 | 36 | 2023 |
| Safari: Sparsity-enabled federated learning with limited and unreliable communications Y Mao, Z Zhao, M Yang, L Liang, Y Liu, W Ding, T Lan, XP Zhang IEEE Transactions on Mobile Computing, 2023 | 10 | 2023 |
| FL-TAC: Enhanced Fine-Tuning in Federated Learning via Low-Rank, Task-Specific Adapter Clustering S Ping, Y Mao, Y Liu, XP Zhang, W Ding arXiv preprint arXiv:2404.15384, 2024 | 1 | 2024 |
| Optimizing Privacy-Accuracy Trade-off in DP-FL via Significant Gradient Perturbation B Zhang, Y Mao, Z Tu, X He, P Pingand, J Wu Proc. of 19th International Conference on Mobility, Sensing, and Networking …, 2023 | 1 | 2023 |
| Local Performance Trade-Off in Heterogeneous Federated Learning with Dynamic Client Grouping Y Mao, J Wu, Y Cheng, P Ping, J Wu 2022 IEEE 19th International Conference on Mobile Ad Hoc and Smart Systems …, 2022 | 1 | 2022 |
| AQUILA: Communication Efficient Federated Learning With Adaptive Quantization in Device Selection Strategy Z Zhao, Y Mao, Z Shi, Y Liu, T Lan, W Ding, XP Zhang IEEE Transactions on Mobile Computing, 2023 | | 2023 |
| AQUILA: Communication Efficient Federated Learning with Adaptive Quantization of Lazily-Aggregated Gradients Z Zhao, Y Mao, Z Shi, Y Liu, T Lan, W Ding, XP Zhang arXiv preprint arXiv:2308.00258, 2023 | | 2023 |
