SAFA: A Semi-Asynchronous Protocol for Fast Federated Learning With Low Overhead

• Published in: IEEE transactions on computers Vol. 70; no. 5; pp. 655 - 668
• Main Authors: Wu, Wentai, He, Ligang, Lin, Weiwei, Mao, Rui, Maple, Carsten, Jarvis, Stephen
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.05.2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Artificial intelligence; Cognitive tasks; Convergence; Crashes; Data models; Distributed computing; Distributed databases; edge intelligence; Efficiency; Federated learning; Machine learning; Model accuracy; Optimization; Protocols; Training

Federated learning (FL) has attracted increasing attention as a promising approach to driving a vast number of end devices with artificial intelligence. However, it is very challenging to guarantee the efficiency of FL considering the unreliable nature of end devices while the cost of device-server...