AI RESEARCH
Personalized Federated Learning by Energy-Efficient UAV Communications
arXiv CS.LG
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ArXi:2605.25212v1 Announce Type: new Federated learning (FL) is an effective paradigm for enhancing the learning capability of edge devices while preserving data privacy. In geographically dispersed FL systems, such as sensor networks in remote areas, unmanned aerial vehicles (UAVs) can flexibly establish high-quality communication links to parameter exchange. However, device heterogeneity and the limited battery capacity of UAVs pose significant challenges.