Open-Source Federated Learning Frameworks for IoT: A Comparative Review and Analysis.

Kholod, Ivan; Yanaki, Evgeny; Fomichev, Dmitry; Shalugin, Evgeniy; Novikova, Evgenia; Filippov, Evgeny; Nordlund, Mats

Kholod, Ivan; Yanaki, Evgeny; Fomichev, Dmitry; Shalugin, Evgeniy; Novikova, Evgenia; Filippov, Evgeny; Nordlund, Mats.

Afiliación

Kholod I; Faculty of Computer Science and Technology, Saint Petersburg Electrotechnical University "LETI", Saint Petersburg 197376, Russia.
Yanaki E; Faculty of Computer Science and Technology, Saint Petersburg Electrotechnical University "LETI", Saint Petersburg 197376, Russia.
Fomichev D; Faculty of Computer Science and Technology, Saint Petersburg Electrotechnical University "LETI", Saint Petersburg 197376, Russia.
Shalugin E; Faculty of Computer Science and Technology, Saint Petersburg Electrotechnical University "LETI", Saint Petersburg 197376, Russia.
Novikova E; Faculty of Computer Science and Technology, Saint Petersburg Electrotechnical University "LETI", Saint Petersburg 197376, Russia.
Filippov E; Smartilizer Rus LLC, Saint Petersburg 197376, Russia.
Nordlund M; AI Sweden, Zenseact AB, Smartilizer Scandinavia AB, 417 56 Goteborg, Sweden.

Sensors (Basel) ; 21(1)2020 Dec 29.

Article en En | MEDLINE | ID: mdl-33383803

Palabras clave

Internet of Things; deep learning; distributed learning; federated learning; machine learning; privacy; smart sensors

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Texto completo: 1 Banco de datos: MEDLINE Idioma: En Revista: Sensors (Basel) Año: 2020 Tipo del documento: Article País de afiliación: Rusia

Texto completo

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XML

PubMed Links

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Texto completo: 1 Banco de datos: MEDLINE Idioma: En Revista: Sensors (Basel) Año: 2020 Tipo del documento: Article País de afiliación: Rusia