Privacy-Preserving Federated Learning
Aurélien BELLET
INRIA Lille
http://researchers.lille.inria.fr/abellet/
Date(s) : 25/03/2022 iCal
14h30 - 15h30
Federated learning (FL) is a machine learning paradigm where several participants collaboratively train a model while keeping their data decentralized. However, the model parameters or gradients exchanged during the FL training process may leak information about the data. After a brief introduction to FL, I will show how to use the notion of Differential Privacy (DP) to design FL algorithms that provably ensure privacy and confidentiality
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