Resource-efficient federated learning with hierarchical aggregation in edge computing Z Wang, H Xu, J Liu, H Huang, C Qiao, Y Zhao IEEE INFOCOM 2021-IEEE conference on computer communications, 1-10, 2021 | 129 | 2021 |
Accelerating federated learning with cluster construction and hierarchical aggregation Z Wang, H Xu, J Liu, Y Xu, H Huang, Y Zhao IEEE Transactions on Mobile Computing 22 (7), 3805-3822, 2022 | 53 | 2022 |
Fedmp: Federated learning through adaptive model pruning in heterogeneous edge computing Z Jiang, Y Xu, H Xu, Z Wang, C Qiao, Y Zhao 2022 IEEE 38th International Conference on Data Engineering (ICDE), 767-779, 2022 | 38 | 2022 |
Communication-efficient asynchronous federated learning in resource-constrained edge computing J Liu, H Xu, Y Xu, Z Ma, Z Wang, C Qian, H Huang Computer Networks 199, 108429, 2021 | 25 | 2021 |
Computation and communication efficient federated learning with adaptive model pruning Z Jiang, Y Xu, H Xu, Z Wang, J Liu, Q Chen, C Qiao IEEE Transactions on Mobile Computing 23 (3), 2003-2021, 2023 | 15 | 2023 |
Enhancing federated learning with intelligent model migration in heterogeneous edge computing J Liu, Y Xu, H Xu, Y Liao, Z Wang, H Huang 2022 IEEE 38th International Conference on Data Engineering (ICDE), 1586-1597, 2022 | 15 | 2022 |
CoopFL: Accelerating federated learning with DNN partitioning and offloading in heterogeneous edge computing Z Wang, H Xu, Y Xu, Z Jiang, J Liu Computer Networks 220, 109490, 2023 | 14 | 2023 |
Finch: Enhancing federated learning with hierarchical neural architecture search J Liu, J Yan, H Xu, Z Wang, J Huang, Y Xu IEEE Transactions on Mobile Computing, 2023 | 13 | 2023 |
Enhancing federated learning with in-cloud unlabeled data L Wang, Y Xu, H Xu, J Liu, Z Wang, L Huang 2022 IEEE 38th International Conference on Data Engineering (ICDE), 136-149, 2022 | 12 | 2022 |
Yoga: Adaptive layer-wise model aggregation for decentralized federated learning J Liu, J Liu, H Xu, Y Liao, Z Wang, Q Ma IEEE/ACM Transactions on Networking, 2023 | 6 | 2023 |
Adaptive control of client selection and gradient compression for efficient federated learning Z Jiang, Y Xu, H Xu, Z Wang, C Qian arXiv preprint arXiv:2212.09483, 2022 | 5 | 2022 |
Heterogeneity-Aware Federated Learning with Adaptive Client Selection and Gradient Compression Z Jiang, Y Xu, H Xu, Z Wang, C Qian IEEE INFOCOM 2023-IEEE Conference on Computer Communications, 1-10, 2023 | 4 | 2023 |
Federated learning with client selection and gradient compression in heterogeneous edge systems Y Xu, Z Jiang, H Xu, Z Wang, C Qian, C Qiao IEEE Transactions on Mobile Computing, 2023 | 3 | 2023 |
Adaptive block-wise regularization and knowledge distillation for enhancing federated learning J Liu, Q Zeng, H Xu, Y Xu, Z Wang, H Huang IEEE/ACM Transactions on Networking, 2023 | 3 | 2023 |
DNN inference acceleration with partitioning and early exiting in edge computing C Li, H Xu, Y Xu, Z Wang, L Huang Wireless Algorithms, Systems, and Applications: 16th International …, 2021 | 3 | 2021 |
FAST: Enhancing Federated Learning Through Adaptive Data Sampling and Local Training Z Wang, H Xu, Y Xu, Z Jiang, J Liu, S Chen IEEE Transactions on Parallel and Distributed Systems, 2023 | 2 | 2023 |
Enhanced federated learning with adaptive block-wise regularization and knowledge distillation Q Zeng, J Liu, H Xu, Z Wang, Y Xu, Y Zhao 2023 IEEE/ACM 31st International Symposium on Quality of Service (IWQoS), 1-4, 2023 | 2 | 2023 |
Enhancing federated learning with server-side unlabeled data by adaptive client and data selection Y Xu, L Wang, H Xu, J Liu, Z Wang, L Huang IEEE Transactions on Mobile Computing 23 (4), 2813-2831, 2023 | 2 | 2023 |
Peaches: Personalized federated learning with neural architecture search in edge computing J Yan, J Liu, H Xu, Z Wang, C Qiao IEEE Transactions on Mobile Computing, 2024 | 1 | 2024 |
Semi-Supervised Decentralized Machine Learning with Device-to-Device Cooperation Z Jiang, Y Xu, H Xu, Z Wang, J Liu, C Qiao IEEE Transactions on Mobile Computing, 2024 | 1 | 2024 |