An Inexact and Self-Adaptive ADMM Algorithm for Federated Learning

The core message of this paper is to propose an inexact and self-adaptive FedADMM algorithm, termed FedADMM-InSa, to address the challenges in current FedADMM methods, including the need to empirically set the local training accuracy and the penalty parameter.