Analysis and Optimization of Wireless Federated Learning with Data Heterogeneity

no code implementations • 4 Aug 2023 • Xuefeng Han, Jun Li, Wen Chen, Zhen Mei, Kang Wei, Ming Ding, H. Vincent Poor

With the rapid proliferation of smart mobile devices, federated learning (FL) has been widely considered for application in wireless networks for distributed model training.

Federated Learning Scheduling

Mobility-Aware Joint User Scheduling and Resource Allocation for Low Latency Federated Learning

no code implementations • 18 Jul 2023 • Kecheng Fan, Wen Chen, Jun Li, Xiumei Deng, Xuefeng Han, Ming Ding

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 aggregating at the central server side, thereby protecting privacy of users.

Federated Learning Scheduling