3 papers
cs.LG2023
A New Interpretable Neural Network-Based Rule Model for Healthcare Decision Making
Adrien Benamira, Tristan Guerand, Thomas Peyrin
In healthcare applications, understanding how machine/deep learning models make decisions is crucial. In this study, we introduce a neural network framework, $\textit{Truth Table r…
cs.AI2023
Neural Network-Based Rule Models With Truth Tables
Adrien Benamira, Tristan Guérand, Thomas Peyrin +1
Understanding the decision-making process of a machine/deep learning model is crucial, particularly in security-sensitive applications. In this study, we introduce a neural network…
cs.CR2023
TT-TFHE: a Torus Fully Homomorphic Encryption-Friendly Neural Network Architecture
Adrien Benamira, Tristan Guérand, Thomas Peyrin +1
This paper presents TT-TFHE, a deep neural network Fully Homomorphic Encryption (FHE) framework that effectively scales Torus FHE (TFHE) usage to tabular and image datasets using a…