Search Results for author: Théo Ryffel

Found 5 papers, 2 papers with code

ARIANN: Low-Interaction Privacy-Preserving Deep Learning via Function Secret Sharing

no code implementations8 Jun 2020 Théo Ryffel, Pierre Tholoniat, David Pointcheval, Francis Bach

We evaluate our end-to-end system for private inference and training on standard neural networks such as AlexNet, VGG16 or ResNet18 between distant servers.

Federated Learning Privacy Preserving Deep Learning

Partially Encrypted Deep Learning using Functional Encryption

1 code implementation NeurIPS 2019 Théo Ryffel, David Pointcheval, Francis Bach, Edouard Dufour-Sans, Romain Gay

Machine learning on encrypted data has received a lot of attention thanks to recent breakthroughs in homomorphic encryption and secure multi-party computation.

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