Proactive Content Caching for Internet-of-Vehicles based on Peer-to-Peer Federated Learning. - Zhengxin Yu; Jia Hu 001; Geyong Min; Han Xu; Jed Mills (ICPADS, 2020)

User-Oriented Multi-Task Federated Deep Learning for Mobile Edge Computing. - Jed Mills; Jia Hu 001; Geyong Min (CoRR, 2020)

Communication-Efficient Federated Learning for Wireless Edge Intelligence in IoT. - Jed Mills; Jia Hu 001; Geyong Min (IEEE Internet Things J., 2020)

Federated Ensemble Model-based Reinforcement Learning. - Jin Wang 024; Jia Hu 001; Jed Mills; Geyong Min (CoRR, 2021)

Client-Side Optimization Strategies for Communication-Efficient Federated Learning. - Jed Mills; Jia Hu 001; Geyong Min (IEEE Commun. Mag., 2022)

Multi-Task Federated Learning for Personalised Deep Neural Networks in Edge Computing. - Jed Mills; Jia Hu 001; Geyong Min (IEEE Trans. Parallel Distributed Syst., 2022)

Accelerating Federated Learning With a Global Biased Optimiser. - Jed Mills; Jia Hu 001; Geyong Min; Rui Jin; Siwei Zheng; Jin Wang 024 (IEEE Trans. Computers, 2023)

Federated Ensemble Model-Based Reinforcement Learning in Edge Computing. - Jin Wang 024; Jia Hu 001; Jed Mills; Geyong Min; Ming Xia; Nektarios Georgalas (IEEE Trans. Parallel Distributed Syst., 2023)

Faster Federated Learning With Decaying Number of Local SGD Steps. - Jed Mills; Jia Hu 001; Geyong Min (IEEE Trans. Parallel Distributed Syst., 2023)

Lightweight Blockchain-Empowered Secure and Efficient Federated Edge Learning. - Rui Jin; Jia Hu 001; Geyong Min; Jed Mills (IEEE Trans. Computers, 2023)