Nov 3, 2022 · In this paper, we systematically present recent advances in the emerging field of FL client selection and its challenges and research opportunities.
Jul 26, 2023 · In this paper, we systematically present recent advances in the emerging field of FL client selection and its challenges and research ...
This article systematically presents recent advances in the emerging field of FL client selection and its challenges and research opportunities to ...
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Nov 3, 2022 · In this paper, we systematically present recent advances in the emerging field of FL client selection and its challenges and research ...
Client Selection in Federated Learning: Principles, Challenges, and Opportunities ... The content you want is available to Zendy users.Already have an account?
To tackle the FL client heterogeneity problem, various client selection algorithms have been developed, showing promising performance improvement. In this paper ...
The most vital open challenges are selecting the optimal number of clients, large-scale scenarios, decentralized ag- gregation, determining an optimal and ...
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Jul 22, 2024 · This survey provides a comprehensive review of client selection methodologies in FL, addressing the challenges and opportunities in this field.
Sep 4, 2023 · This paper brings the scattered FL client(s) selection models onto a single platform by first categorizing them into five categories.
It is thus essential to design a client selection strategy to choose an appropriate subset of the clients to participate in federated learning.
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