| Decentralized federated learning: A segmented gossip approach C Hu, J Jiang, Z Wang arXiv preprint arXiv:1908.07782, 2019 | 207 | 2019 |
| JALAD: Joint accuracy-and latency-aware deep structure decoupling for edge-cloud execution H Li, C Hu, J Jiang, Z Wang, Y Wen, W Zhu 2018 IEEE 24th international conference on parallel and distributed systems …, 2018 | 145 | 2018 |
| Distributed inference with deep learning models across heterogeneous edge devices C Hu, B Li IEEE INFOCOM 2022-IEEE Conference on Computer Communications, 330-339, 2022 | 47 | 2022 |
| Bacombo—bandwidth-aware decentralized federated learning J Jiang, L Hu, C Hu, J Liu, Z Wang Electronics 9 (3), 440, 2020 | 45 | 2020 |
| Joint model and data adaptation for cloud inference serving J Jiang, Z Luo, C Hu, Z He, Z Wang, S Xia, C Wu 2021 IEEE Real-Time Systems Symposium (RTSS), 279-289, 2021 | 17 | 2021 |
| Caching in dynamic environments: A near-optimal online learning approach S Zhou, Z Wang, C Hu, Y Mao, H Yan, S Zhang, C Wu, W Zhu IEEE Transactions on Multimedia 25, 792-804, 2021 | 15 | 2021 |
| MASKCRYPT: Federated Learning with Selective Homomorphic Encryption C Hu, B Li IEEE Transactions on Dependable and Secure Computing, 2024 | 3 | 2024 |
| TITANIC: Towards Production Federated Learning with Large Language Models N Su, C Hu, B Li, B Li IEEE INFOCOM, 2024 | 2 | 2024 |
| When the Edge Meets Transformers: Distributed Inference with Transformer Models C Hu, B Li 2024 IEEE 44th International Conference on Distributed Computing Systems …, 2024 | | 2024 |
