Federated machine learning in data-protection-compliant research

Link:

https://doi.org/10.1038/s42256-022-00601-5

Autor/in:

Brauneck, Alissa
Schmalhorst, Louisa
Kazemi Majdabadi, Mohammad Mahdi
Bakhtiari, Mohammad
Völker, Uwe
Saak, Christina Caroline; id_orcid 0000-0001-7041-8531
Baumbach, Jan; id_orcid 0000-0002-0282-0462

Erscheinungsjahr:

2023

Medientyp:

Text

Beschreibung:

To fully leverage big data, they need to be shared across institutions in a manner compliant with privacy considerations and the EU General Data Protection Regulation (GDPR). Federated machine learning is a promising option.

Lizenz:

info:eu-repo/semantics/closedAccess

Quellsystem:

Forschungsinformationssystem der UHH

Interne Metadaten

Quelldatensatz: oai:www.edit.fis.uni-hamburg.de:publications/ce658f88-c7e0-48a7-84b4-353bb747f0f1