GossipFL: A Decentralized Federated Learning Framework With Sparsified and Adaptive Communication

• Published in: IEEE transactions on parallel and distributed systems Vol. 34; no. 3; pp. 909 - 922
• Main Authors: Tang, Zhenheng, Shi, Shaohuai, Li, Bo, Chu, Xiaowen
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.03.2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Artificial neural networks; Bandwidth; Bandwidths; Clients; Communication; communication efficiency; Communications traffic; Convergence; Data models; Deep learning; Federated learning; Machine learning; Model accuracy; Servers; Topology; Training

Recently, federated learning (FL) techniques have enabled multiple users to train machine learning models collaboratively without data sharing. However, existing FL algorithms suffer from the communication bottleneck due to network bandwidth pressure and/or low bandwidth utilization of the participa...