| CREAT: Blockchain-assisted compression algorithm of federated learning for content caching in edge computing L Cui, X Su, Z Ming, Z Chen, S Yang, Y Zhou, W Xiao IEEE Internet of Things Journal 9 (16), 14151-14161, 2020 | 135 | 2020 |
| Slashing communication traffic in federated learning by transmitting clustered model updates L Cui, X Su, Y Zhou, Y Pan IEEE Journal on Selected Areas in Communications 39 (8), 2572-2589, 2021 | 39 | 2021 |
| Optimal rate adaption in federated learning with compressed communications L Cui, X Su, Y Zhou, J Liu IEEE INFOCOM 2022-IEEE Conference on Computer Communications, 1459-1468, 2022 | 38 | 2022 |
| A fast blockchain-based federated learning framework with compressed communications L Cui, X Su, Y Zhou IEEE Journal on Selected Areas in Communications 40 (12), 3358-3372, 2022 | 32 | 2022 |
| On model transmission strategies in federated learning with lossy communications X Su, Y Zhou, L Cui, J Liu IEEE Transactions on Parallel and Distributed Systems 34 (4), 1173-1185, 2023 | 25 | 2023 |
| ClusterGrad: Adaptive gradient compression by clustering in federated learning L Cui, X Su, Y Zhou, L Zhang GLOBECOM 2020-2020 IEEE Global Communications Conference, 1-7, 2020 | 18 | 2020 |
| Expediting In-Network Federated Learning by Voting-Based Consensus Model Compression X Su, Y Zhou, L Cui, S Guo arXiv preprint arXiv:2402.03815, 2024 | 2 | 2024 |
| Fed-CVLC: Compressing federated learning communications with variable-length codes X Su, Y Zhou, L Cui, JCS Lui, J Liu IEEE INFOCOM 2024-IEEE Conference on Computer Communications, 601-610, 2024 | 1 | 2024 |
| Fast-Convergent Wireless Federated Learning: A Voting Based TopK Model Compression Approach X Su, Y Zhou, L Cui, QZ Sheng, Y Wang, S Guo IEEE Journal on Selected Areas in Communications, 2024 | | 2024 |
