Accelerating Federated Edge Learning via Optimized Probabilistic Device Scheduling
Accelerating Federated Edge Learning via Optimized Probabilistic Device Scheduling
The popular federated edge learning (FEEL) framework allows privacy-preserving collaborative model training via frequent learning-updates exchange between edge devices and server. Due to the constrained bandwidth, only a subset of devices can upload their updates at each communication round. This has led to an active research area in FEEL studying …