most citedPersonalized Federated Learning over non-IID Data for Indoor Localization

2 citations · 2 across the 1 of their papers we have counts for

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1 paper

cs.LG2021★ 2 cited

Personalized Federated Learning over non-IID Data for Indoor Localization

Peng Wu, Tales Imbiriba, Junha Park +2

Localization and tracking of objects using data-driven methods is a popular topic due to the complexity in characterizing the physics of wireless channel propagation models. In the…