Flotilla: A scalable, modular and resilient federated learning framework for heterogeneous resources

With the recent improvements in mobile and edge computing and rising concerns of data privacy, Federated Learning (FL) has rapidly gained popularity as a privacy-preserving, distributed machine learning methodology. Several FL frameworks have been built for testing novel FL strategies. However, most...

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Bibliographische Detailangaben

Veröffentlicht in:	Journal of parallel and distributed computing Jg. 203; S. 105103
Hauptverfasser:	Banerjee, Roopkatha, Modi, Prince, Vyas, Jinal, Sri Abhijit, Chunduru, Chandrashekar, Tejus, Marisetty, Harsha Varun, Gupta, Manik, Simmhan, Yogesh
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Inc 01.09.2025
Schlagworte:	Distributed programming Edge intelligence Federated learning Federated learning Distributed programming Edge intelligence
ISSN:	0743-7315
Online-Zugang:	Volltext
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