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Resource-efficient clustering collaborative federated learning client selection method
更新时间：2026-02-03

    • Resource-efficient clustering collaborative federated learning client selection method

    • “Experts propose a resource efficient clustering collaborative federated learning client selection method to address the heterogeneity of client resources and data in federated learning. Experiments show that this method can reduce global training time and achieve a good balance between training efficiency and global model accuracy.”
    • Journal of Jilin University(Engineering and Technology Edition)   Vol. 55, Issue 10, Pages: 3337-3345(2025)
    • 作者机构：

      吉林大学 计算机科学与技术学院，长春 130012

    • DOI：10.13229/j.cnki.jdxbgxb.20231369    

      CLC： TP301

    • Received：08 December 2023，

      Published：01 October 2025

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  • LI Qiang,ZHANG Ling-yu,MENG Xiang-yu.Resource-efficient clustering collaborative federated learning client selection method[J].Journal of Jilin University(Engineering and Technology Edition),2025,55(10):3337-3345. DOI： 10.13229/j.cnki.jdxbgxb.20231369.

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