35 citations · 61 across the 10 of their papers we have counts for
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eess.SP2022★ 1 cited
UAV-Assisted Hierarchical Aggregation for Over-the-Air Federated Learning
Xiangyu Zhong, Xiaojun Yuan, Huiyuan Yang +1
With huge amounts of data explosively increasing in the mobile edge, over-the-air federated learning (OA-FL) emerges as a promising technique to reduce communication costs and priv…
cs.LG2022★ 35 cited
Confederated Learning: Federated Learning with Decentralized Edge Servers
Bin Wang, Jun Fang, Hongbin Li +2
Federated learning (FL) is an emerging machine learning paradigm that allows to accomplish model training without aggregating data at a central server. Most studies on FL consider…