We propose a real-time and on-demand client selection mechanism that employs the DBSCAN (Density-Based Spatial clustering of Applications with Noise) ...
One of the problems in the realm of FL is the issue of client selection where the central server should select the best combination of clients for faster model.
It offers a thorough grasp of the various techniques by discussing two major groups of client selection methods based on the metrics and procedures employed.
Aug 16, 2021 · Specifically, we introduce a client selection approach that leverages the devices' heterogeneity to schedule the clients based on their ...
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Towards Instant Clustering Approach for Federated Learning Client Selection ; International Conference on Computing, Networking and Communications (ICNC 2023).
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May 22, 2024 · In this study, we propose a novel client selection strategy designed to emulate the performance achieved with full client participation.
Towards Instant Clustering Approach for Federated Learning Client Selection · Computer Science. 2023 International Conference on Computing… · 2023.
Aug 18, 2024 · This paper outlines strategies for effective client selection strategies and solutions for ensuring system scalability and stability. Using the ...
In every round, the FedSS server chooses a cluster in a round-robin way and selects clients within it randomly to ensure equal opportunity of every client.
In this work, for the first time, we propose selecting participating clients for each cluster with active learning (AL) and call our method active client ...
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