We propose an intelligent client selection approach for federated learning on IoT devices using matching game theory.

To overcome this problem, we propose an intelligent client selection approach for federated learning on IoT devices using matching game theory. Our solution ...

May 28, 2023 · To overcome this problem, we propose an intelligent client selection approach for federated learning on IoT devices using matching game theory.

Dive into the research topics of 'Towards Bilateral Client Selection in Federated Learning Using Matching Game Theory'. Together they form a unique fingerprint.

Towards Bilateral Client Selection in Federated Learning Using Matching Game Theory · Lebanese American University,Department of Computer Science and Mathematics ...

Motivated by these shortcomings of the random client selection approach, we propose a novel client selection approach for federated learning on IoT devices.

Co-authors ; Towards bilateral client selection in federated learning using matching game theory. O Wehbi, S Arisdakessian, OA Wahab, H Otrok, S Otoum, A Mourad.

Oct 31, 2022 · To overcome this problem, we present in this paper FedMint, an intelligent client selection approach for federated learning on IoT devices using ...

2023. Towards bilateral client selection in federated learning using matching game theory. O Wehbi, S Arisdakessian, OA Wahab, H Otrok, S Otoum, A Mourad.

Dec 1, 2023 · To overcome this problem, we present in this article FedMint, an intelligent client selection approach for FL on IoT devices using game theory ...