50 citations · 113 across the 7 of their papers we have counts for
4 papers · 1 filter
Imperceptible Adversarial Attacks on Tabular Data
Vincent Ballet, Xavier Renard, Jonathan Aigrain +3
Security of machine learning models is a concern as they may face adversarial attacks for unwarranted advantageous decisions. While research on the topic has mainly been focusing o…
Concept Tree: High-Level Representation of Variables for More Interpretable Surrogate Decision Trees
Xavier Renard, Nicolas Woloszko, Jonathan Aigrain +1
Interpretable surrogates of black-box predictors trained on high-dimensional tabular datasets can struggle to generate comprehensible explanations in the presence of correlated var…
Detecting Potential Local Adversarial Examples for Human-Interpretable Defense
Xavier Renard, Thibault Laugel, Marie-Jeanne Lesot +2
Machine learning models are increasingly used in the industry to make decisions such as credit insurance approval. Some people may be tempted to manipulate specific variables, such…
Inverse Classification for Comparison-based Interpretability in Machine Learning
Thibault Laugel, Marie-Jeanne Lesot, Christophe Marsala +2
In the context of post-hoc interpretability, this paper addresses the task of explaining the prediction of a classifier, considering the case where no information is available, nei…