18 citations · 21 across the 6 of their papers we have counts for
6 papers
Regional Explanations: Bridging Local and Global Variable Importance
Salim I. Amoukou, Nicolas J-B. Brunel
We analyze two widely used local attribution methods, Local Shapley Values and LIME, which aim to quantify the contribution of a feature value to a specific prediction $f(x_1…
Adaptive Conformal Prediction by Reweighting Nonconformity Score
Salim I. Amoukou, Nicolas J. B Brunel
Despite attractive theoretical guarantees and practical successes, Predictive Interval (PI) given by Conformal Prediction (CP) may not reflect the uncertainty of a given model. Thi…
Local and Regional Counterfactual Rules: Summarized and Robust Recourses
Salim I. Amoukou, Nicolas J. B Brunel
Counterfactual Explanations (CE) face several unresolved challenges, such as ensuring stability, synthesizing multiple CEs, and providing plausibility and sparsity guarantees. From…
Robust PCA for Anomaly Detection and Data Imputation in Seasonal Time Series
Hong-Lan Botterman, Julien Roussel, Thomas Morzadec +2
We propose a robust principal component analysis (RPCA) framework to recover low-rank and sparse matrices from temporal observations. We develop an online version of the batch temp…
MAPIE: an open-source library for distribution-free uncertainty quantification
Vianney Taquet, Vincent Blot, Thomas Morzadec +2
Estimating uncertainties associated with the predictions of Machine Learning (ML) models is of crucial importance to assess their robustness and predictive power. In this submissio…
The Shapley Value of coalition of variables provides better explanations
Salim I. Amoukou, Nicolas J-B. Brunel, Tangi Salaün
While Shapley Values (SV) are one of the gold standard for interpreting machine learning models, we show that they are still poorly understood, in particular in the presence of cat…