FLEX: Robust client selection for dynamic federated learning environments

Mao Li

doi:10.1016/j.knosys.2026.116014

2026-04-25

PRE

DOI：10.1016/j.knosys.2026.116014

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摘要

En 中文

• FLEX：通过变化检测和自适应重启实现动态联邦学习的新型客户端选择。 • Page-Hinckley框架监测客户端贡献，并提供可证明的检测保证。 • 自适应阈值通过提高50%–200%的后期检测灵敏度，实现了高效提升。 • 相比基线方法，实现了94.2%的性能保持和2–3倍更快的收敛速度。

Keyword:

Federated Learning

Client Selection

Change Detection

Adaptive Restart

Dynamic Environments

期刊

Knowledge-Based Systems

IF:

7.6

论文数:

1.3W

被引数:

4.5W

机构

Guangzhou University of Chinese Medicine

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1.7W

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Guangdong Police College

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论文数: 29

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Clemson University

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1.3W

论文数: 1.1W

被引数: 1.4W

south china university of technology

学者数:

6.8W

论文数: 5.1W

被引数: 85

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