Online Learning from data streams via decentralized and asynchronous SGD

Online Learning (OL) is a sub-field of Machine Learning (ML) which focuses on solving time-sensitive problems through iterative learning from data streams. This emerging field is characterized by the challenge of concept drifts, where the underlying distribution of the incoming data values evolves o...

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Veröffentlicht in:	Future generation computer systems Jg. 175; S. 108052
Hauptverfasser:	Tosi, Mauro Dalle Lucca, Theobald, Martin
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 01.02.2026
Schlagworte:	Artificial neural networks Asynchronous & decentralized SGD Concept drifts Data streams Online Learning Online Learning Data streams Concept drifts Asynchronous & decentralized SGD Artificial neural networks
ISSN:	0167-739X
Online-Zugang:	Volltext
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