Federated Learning Under Intermittent Client Availability and Time-Varying Communication Constraints

Federated learning systems facilitate the training of global models across large numbers of distributed edge-devices with potentially heterogeneous data. Such systems operate in resource constrained settings with intermittent client availability and/or time-varying communication constraints. As a re...

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Veröffentlicht in:IEEE journal of selected topics in signal processing 2023-01, Vol.17 (1), p.1-17
Hauptverfasser: Ribero, Monica, Vikalo, Haris, Veciana, Gustavo de
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Sprache:eng
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