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Secure Federated Learning Algorithms for Vertical and Combined Data Partitioning

With the growing need for collaborative machine learning across institutions holding sensitive data, ensuring data privacy without compromising model performance has become an important challenge. This work introduces secure federated learning algorithms that use encryption and masking techniques to...

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Uloženo v:
Hlavní autoři: Amir Anees, Ding Ming, Gnana Bharathy, Lois Holloway
Médium: Artigo
Jazyk:Inglês
Vydáno: MDPI AG 2026-06-01
Edice:Future Internet
Témata:
federated learning
vertical data partitioning
combined data partitioning
gradient inversion attack
data privacy
secure data sharing
On-line přístup:https://www.mdpi.com/1999-5903/18/6/302
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