Communication-efficient federated learning for edge IoT via combined quantization and sparsification
Edge IoT devices are increasingly targeted for on-device intelligence using federated learning (FL). However, conventional FL imposes heavy communication and energy costs that make it impractical for battery-constrained, bandwidth-limited deployments with heterogeneous (non-IID) data. In this paper we present a practic...