An efficient federated learning method based on the proportional-integral-derivative mechanism for embedded devices
For federated learning (FL) deployed on embedded devices, clients (embedded devices) face severe data skew and diverse hardware capabilities. This leads to both data and computational heterogeneity, and the level of heterogeneity varies from device to device. To address the above challenges, this paper proposes an effi...