FedBoost: Bayesian Estimation Based Client Selection for Federated Learning

FedBoost: Bayesian Estimation Based Client Selection for Federated Learning

Although federated learning (FL) represents a distributed machine learning paradigm that ensures privacy protection, the failure of stragglers to upload local models in a timely manner results in an overall degradation of the global model’s performance, and the difficulty of accurately pr...

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Bibliographic Details
Main Authors: Yuhang Sheng, Lingguo Zeng, Shuqin Cao, Qing Dai, Shasha Yang, Jianfeng Lu
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Bayesian estimation
client selection
federated learning
Lyapunov optimization
Online Access:https://ieeexplore.ieee.org/document/10496079/

Internet

https://ieeexplore.ieee.org/document/10496079/

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