3 papers
cs.NI2026
Forecasting-Driven Stable Successor Matching for UAV-Assisted Continuous Edge Services
Houyi Qi, Minghui Liwang, Yuhan Su +1
Continuous and reliable service support is crucial for emerging latency-sensitive and computation-intensive applications in UAV-assisted edge networks (UENs) due to operational dyn…
cs.LG2025
Adaptive UAV-Assisted Hierarchical Federated Learning: Optimizing Energy, Latency, and Resilience for Dynamic Smart IoT
Xiaohong Yang, Minghui Liwang, Liqun Fu +4
Hierarchical Federated Learning (HFL) extends conventional Federated Learning (FL) by introducing intermediate aggregation layers, enabling distributed learning in geographically d…
cs.LG2025
Towards Seamless Hierarchical Federated Learning under Intermittent Client Participation: A Stagewise Decision-Making Methodology
Minghong Wu, Minghui Liwang, Yuhan Su +5
Federated Learning (FL) offers a pioneering distributed learning paradigm that enables devices/clients to build a shared global model. This global model is obtained through frequen…