39 citations · 41 across the 2 of their papers we have counts for
2 papers
cs.LG2023★ 2 cited
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…
cs.LG2022★ 39 cited
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…