| Deep reinforcement learning-based server selection for mobile edge computing H Liu, G Cao IEEE Transactions on Vehicular Technology 70 (12), 13351-13363, 2021 | 37 | 2021 |
| Communication-efficient federated learning for heterogeneous edge devices based on adaptive gradient quantization H Liu, F He, G Cao IEEE INFOCOM 2023-IEEE Conference on Computer Communications, 1-10, 2023 | 35 | 2023 |
| Deep learning video analytics through online learning based edge computing H Liu, G Cao IEEE Transactions on Wireless Communications 21 (10), 8193-8204, 2022 | 15 | 2022 |
| Energy efficient medium access scheme for visible light communication system based on IEEE 802.15. 7 with unsaturated traffic H Liu, L Zhang, M Jiang IET Communications 10 (18), 2534-2542, 2016 | 9 | 2016 |
| A successive transmission medium access scheme with dynamic contention window for VLC system with saturated traffic H Liu, L Zhang, Z Wu Photonic Network Communications 34, 63-74, 2017 | 8 | 2017 |
| HoneyIoT: Adaptive High-Interaction Honeypot for IoT Devices Through Reinforcement Learning C Guan, H Liu, G Cao, S Zhu, T La Porta Proceedings of the 16th ACM Conference on Security and Privacy in Wireless …, 2023 | 6 | 2023 |
| A medium access scheme with dynamic contention window-based successive transmission for visible light communications system H Liu, L Zhang 2016 International Conference on Information and Communication Technology …, 2016 | 6 | 2016 |
| Predicting GPU Failures With High Precision Under Deep Learning Workloads H Liu, Z Li, C Tan, R Yang, G Cao, Z Liu, C Guo Proceedings of the 16th ACM International Conference on Systems and Storage …, 2023 | 3 | 2023 |
| Prediction of GPU failures under deep learning workloads H Liu, Z Li, C Tan, R Yang, G Cao, Z Liu, C Guo arXiv preprint arXiv:2201.11853, 2022 | 1 | 2022 |
