A Client Selection Method Based on Loss Function Optimization for Federated Learning

Author:

Zeng Yan,Teng Siyuan,Xiang Tian,Zhang Jilin,Mu Yuankai,Ren Yongjian,Wan Jian

Publisher

Computers, Materials and Continua (Tech Science Press)

Subject

Computer Science Applications,Modeling and Simulation,Software

Reference38 articles.

1. A study of mobile device utilization;Gao,2015

2. Federated learning model training method based on data features perception aggregation;Zeng,2021

3. Machine learning applications in drug repurposing;Yang;Interdisciplinary Sciences: Computational Life Sciences,2022

4. Learning from others without sacrificing privacy: Simulation comparing centralized and federated machine learning on mobile health data;Liu;JMIR mHealth and uHealth,2021

5. What the gdpr means for businesses;Tankard;Network Security,2016

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Technical considerations of federated learning in digital healthcare systems;Federated Learning for Digital Healthcare Systems;2024

2. FedAG:A Federated Learning Method Based on Data Importance Weighted Aggregation;2023 IEEE/CIC International Conference on Communications in China (ICCC);2023-08-10

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