125 citations · 385 across the 9 of their papers we have counts for
3 papers · 1 filter
SRATTA : Sample Re-ATTribution Attack of Secure Aggregation in Federated Learning
Tanguy Marchand, Régis Loeb, Ulysse Marteau-Ferey +2
We consider a cross-silo federated learning (FL) setting where a machine learning model with a fully connected first layer is trained between different clients and a central server…
SecureFedYJ: a safe feature Gaussianization protocol for Federated Learning
Tanguy Marchand, Boris Muzellec, Constance Beguier +2
The Yeo-Johnson (YJ) transformation is a standard parametrized per-feature unidimensional transformation often used to Gaussianize features in machine learning. In this paper, we i…
FLamby: Datasets and Benchmarks for Cross-Silo Federated Learning in Realistic Healthcare Settings
Jean Ogier du Terrail, Samy-Safwan Ayed, Edwige Cyffers +21
Federated Learning (FL) is a novel approach enabling several clients holding sensitive data to collaboratively train machine learning models, without centralizing data. The cross-s…