3 papers
cs.DC2024
Energy-Efficient Wireless Federated Learning via Doubly Adaptive Quantization
Xuefeng Han, Wen Chen, Jun Li +5
Federated learning (FL) has been recognized as a viable distributed learning paradigm for training a machine learning model across distributed clients without uploading raw data. H…
cs.LG2023
Analysis and Optimization of Wireless Federated Learning with Data Heterogeneity
Xuefeng Han, Jun Li, Wen Chen +4
With the rapid proliferation of smart mobile devices, federated learning (FL) has been widely considered for application in wireless networks for distributed model training. Howeve…
cs.DC2023
Mobility-Aware Joint User Scheduling and Resource Allocation for Low Latency Federated Learning
Kecheng Fan, Wen Chen, Jun Li +3
As an efficient distributed machine learning approach, Federated learning (FL) can obtain a shared model by iterative local model training at the user side and global model aggrega…