Enhancing Differential Privacy for Federated Learning at Scale

Federated learning (FL) is an emerging technique that trains machine learning models across multiple de-centralized systems. It enables local devices to collaboratively learn a model by aggregating locally computed updates via a server. Privacy is a core aspect of FL, and recent works in this area a...

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Autores principales: Chunghun Baek, Sungwook Kim, Dongkyun Nam, Jihoon Park
Formato: article
Lenguaje:EN
Publicado: IEEE 2021
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Acceso en línea:https://doaj.org/article/ca4f5cebcb204fb6adf064ce48a9d83f
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