Client Selection
Client Selection is a strategic process in federated learning that determines which participating devices or data providers are chosen for model training in each communication round, distinguishing it from other resource allocation mechanisms by its focus on optimizing performance, fairness, and efficiency under constraints such as heterogeneity, availability, and communication costs.
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11K
Citations
602
Authors
252
Institutions
Publications per year
2017–2026
139
Parents
188
Client Selection in Federated Learning: Principles, Challenges, and Opportunities
Lei Fu, Huanle Zhang, Ge Gao et al. · IEEE Internet of Things Journal · 2023 · 263 citations
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South China University of Technology
Guangzhou, China
9 h-index
23 publications
2.3K citations
Nanyang Technological University
Singapore, Singapore
8 h-index
23 publications
1.2K citations

Shanghai Jiao Tong University
Shanghai, China
7 h-index
15 publications
599 citations
Peng Cheng Laboratory
Shenzhen, China
7 h-index
9 publications
457 citations

Chinese Academy of Sciences
Beijing, China
6 h-index
11 publications
566 citations
ShanghaiTech University
Shanghai, China
5 h-index
20 publications
1.2K citations
Shanghai Advanced Research Institute
Pudong, China
5 h-index
10 publications
540 citations
Tsinghua University
Beijing, China
5 h-index
18 publications
1.5K citations
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18 publications · 1.3K citations
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Repository · 12 publications · 491 citations
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TPDS · 7 publications · 820 citations
7
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5 publications · 637 citations
4
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4 publications · 327 citations
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