Cafe : Improved Federated Data Imputation by Leveraging Missing Data Heterogeneity

Federated learning (FL), a decentralized machine learning approach, offers great performance while alleviating autonomy and confidentiality concerns. Despite FL's popularity, how to deal with missing values in a federated manner is not well understood. In this work, we initiate a study of feder...

Description complète

Détails bibliographiques

Publié dans:	IEEE transactions on knowledge and data engineering. - 1998. - 37(2025), 5 vom: 28. Mai, Seite 2266-2281
Auteur principal:	Min, Sitao (Auteur)
Autres auteurs:	Asif, Hafiz, Wang, Xinyue, Vaidya, Jaideep
Format:	Article en ligne
Langue:	English
Publié:	2025
Accès à la collection:	IEEE transactions on knowledge and data engineering
Sujets:	Journal Article Data Heterogeneity Data Quality Federated Learning Missing Data Imputation