| Communication-efficient federated learning for wireless edge intelligence in IoT J Mills, J Hu, G Min IEEE Internet of Things Journal 7 (7), 5986-5994, 2019 | 333 | 2019 |
| Multi-Task Federated Learning for Personalised Deep Neural Networks in Edge Computing J Mills, J Hu, G Min IEEE Transactions on Parallel and Distributed Systems 33 (3), 630-641, 2021 | 128 | 2021 |
| Proactive Content Caching for Internet-of-Vehicles based on Peer-to-Peer Federated Learning Z Yu, J Hu, G Min, H Xu, J Mills 2020 IEEE 26th International Conference on Parallel and Distributed Systems …, 2020 | 39 | 2020 |
| Client-Side Optimization Strategies for Communication-Efficient Federated Learning J Mills, J Hu, G Min IEEE Communications Magazine 60 (7), 60-66, 2022 | 9 | 2022 |
| Accelerating federated learning with a global biased optimiser J Mills, J Hu, G Min, R Jin, S Zheng, J Wang IEEE Transactions on Computers, 2022 | 6 | 2022 |
| Federated ensemble model-based reinforcement learning J Wang, J Hu, J Mills, G Min CoRR, 2021 | 6* | 2021 |
| Lightweight Blockchain-empowered Secure and Efficient Federated Edge Learning R Jin, J Hu, G Min, J Mills IEEE Transactions on Computers, 2023 | 4 | 2023 |
| Faster Federated Learning with Decaying Number of Local SGD Steps J Mills, J Hu, G Min IEEE Transactions on Parallel and Distributed Systems, 2023 | 2 | 2023 |
| Federated Machine Learning in Edge Computing J Mills PQDT-Global, 2022 | | 2022 |
