Enhancing Efficiency in Federated Learning for Constrained Devices through Selective Data Training

Centaur, an end-to-end federated learning framework, enhances efficiency in multidevice federated learning by incorporating on-device data selection and partition-based model training to address the resource constraints of ubiquitous constrained devices.