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arXiv · 2310.09370

Near-optimal Differentially Private Client Selection in Federated Settings

Syed Eqbal Alam·Dhirendra Shukla·Shrisha Rao
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Abstract

We develop an iterative differentially private algorithm for client selection in federated settings. We consider a federated network wherein clients coordinate with a central server to complete a task; however, the clients decide whether to participate or not at a time step based on their preferences -- local computation and probabilistic intent. The algorithm does not require client-to-client information exchange. The developed algorithm provides near-optimal values to the clients over long-term average participation with a certain differential privacy guarantee. Finally, we present the experimental results to check the algorithm's efficacy.

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Syed Eqbal Alam, Dhirendra Shukla, Shrisha Rao. 2023-10-13. Near-optimal Differentially Private Client Selection in Federated Settings. https://arxiv.org/abs/2310.09370

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