Byzantine-resilient decentralized stochastic gradient descent

• Main Authors: GUO, Shangwei, ZHANG, Tianwei, YU, Han, XIE, Xiaofei, MA, Lei, XIANG, Tao, LIU, Yang
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2022
• Subjects: Training; servers; learning systems; distance learning; computer aided instruction; security; fault tolerant systems; decentralized learning; stochastic gradient descent; Byzantine attack; Byzantine fault tolerance; Artificial Intelligence and Robotics; Theory and Algorithms
• Online Access: https://ink.library.smu.edu.sg/sis_research/7827
• Institution: Singapore Management University

Decentralized learning has gained great popularity to improve learning efficiency and preserve data privacy. Each computing node makes equal contribution to collaboratively learn a Deep Learning model. The elimination of centralized Parameter Servers (PS) can effectively address many issues such as...