14 citations · 21 across the 6 of their papers we have counts for
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cs.LG2020★ 1 cited
ARIANN: Low-Interaction Privacy-Preserving Deep Learning via Function Secret Sharing
Théo Ryffel, Pierre Tholoniat, David Pointcheval +1
We propose AriaNN, a low-interaction privacy-preserving framework for private neural network training and inference on sensitive data. Our semi-honest 2-party computation protocol…
cs.LG2019★ 14 cited
Partially Encrypted Machine Learning using Functional Encryption
Theo Ryffel, Edouard Dufour-Sans, Romain Gay +2
Machine learning on encrypted data has received a lot of attention thanks to recent breakthroughs in homomorphic encryption and secure multi-party computation. It allows outsourcin…