2 papers
cs.LG2025
Rethinking Federated Learning Over the Air: The Blessing of Scaling Up
Jiaqi Zhu, Bikramjit Das, Yong Xie +2
Federated learning facilitates collaborative model training across multiple clients while preserving data privacy. However, its performance is often constrained by limited communic…
cs.LG2025
Robust Federated Learning Over the Air: Combating Heavy-Tailed Noise with Median Anchored Clipping
Jiaxing Li, Zihan Chen, Kai Fong Ernest Chong +3
Leveraging over-the-air computations for model aggregation is an effective approach to cope with the communication bottleneck in federated edge learning. By exploiting the superpos…