Performance Optimization for Variable Bitwidth Federated Learning in Wireless Networks
Performance Optimization for Variable Bitwidth Federated Learning in Wireless Networks
This paper considers improving wireless communication and computation efficiency in federated learning (FL) via model quantization. In the proposed bitwidth FL scheme, edge devices train and transmit quantized versions of their local FL model parameters to a coordinating server, which, in turn, aggregates them into a quantized global model and …