313 citations · 654 across the 61 of their papers we have counts for
4 papers · 2 filters
Timely Parameter Updating in Over-the-Air Federated Learning
Jiaqi Zhu, Zhongyuan Zhao, Xiao Li +3
Incorporating over-the-air computations (OAC) into the model training process of federated learning (FL) is an effective approach to alleviating the communication bottleneck in FL…
Feature-Based Semantics-Aware Scheduling for Energy-Harvesting Federated Learning
Eunjeong Jeong, Giovanni Perin, Howard H. Yang +1
Federated Learning (FL) on resource-constrained edge devices faces a critical challenge: The computational energy required for training Deep Neural Networks (DNNs) often dominates…
Accelerating Wireless Distributed Learning via Hybrid Split and Federated Learning Optimization
Kun Guo, Xuefei Li, Xijun Wang +3
Federated learning (FL) and split learning (SL) are two effective distributed learning paradigms in wireless networks, enabling collaborative model training across mobile devices w…
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…