| ESync: Accelerating intra-domain federated learning in heterogeneous data centers Z Li, H Zhou, T Zhou, H Yu, Z Xu, G Sun IEEE Transactions on Services Computing 15 (4), 2261-2274, 2020 | 29 | 2020 |
| Online job scheduling for distributed machine learning in optical circuit switch networks L Liu, H Yu, G Sun, H Zhou, Z Li, S Luo Knowledge-Based Systems 201, 106002, 2020 | 17 | 2020 |
| DGT: A contribution-aware differential gradient transmission mechanism for distributed machine learning H Zhou, Z Li, Q Cai, H Yu, S Luo, L Luo, G Sun Future Generation Computer Systems 121, 35-47, 2021 | 11 | 2021 |
| TSEngine: Enable efficient communication overlay in distributed machine learning in WANs H Zhou, W Cai, Z Li, H Yu, L Liu, L Luo, G Sun IEEE Transactions on Network and Service Management 18 (4), 4846-4859, 2021 | 10 | 2021 |
| NBSync: Parallelism of local computing and global synchronization for fast distributed machine learning in WANs H Zhou, Z Li, H Yu, L Luo, G Sun IEEE Transactions on Services Computing 16 (6), 4115-4127, 2023 | 4 | 2023 |
| DGT: A communication-efficient differential gradient transmission protocol for distributed deep learning H Zhou, Z Li, H Yu Proc. Asia-Pacific Workshop Netw., 1-2, 2019 | 1 | 2019 |
| FedGSync: Jointly Optimized Weak Synchronization and Gradient Transmission for Fast Distributed Machine Learning in Heterogeneous WAN H Zhou, Y He, Z Zhang, L Luo, H Yu, G Sun 2023 IEEE International Conference on Systems, Man, and Cybernetics (SMC …, 2023 | | 2023 |