STAFL: Staleness-Tolerant Asynchronous Federated Learning on Non-iid Dataset

STAFL: Staleness-Tolerant Asynchronous Federated Learning on Non-iid Dataset

With the development of the Internet of Things, edge computing applications are paying more and more attention to privacy and real-time. Federated learning, a promising machine learning method that can protect user privacy, has begun to be widely studied. However, traditional synchronous federated l...

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Bibliographic Details
Main Authors: Feng Zhu, Jiangshan Hao, Zhong Chen, Yanchao Zhao, Bing Chen, Xiaoyang Tan
Format: Article
Language:English
Published: MDPI AG 2022-01-01
Series:Electronics
Subjects:
federated learning
edge computing
weight divergence
non-iid
Online Access:https://www.mdpi.com/2079-9292/11/3/314

Internet

https://www.mdpi.com/2079-9292/11/3/314

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