From the 2 of 20 linked papers with an AI index.
20 papers
OT-FairBoost: Optimal Transport-Guided Gradient Boosting for Fairness Regularization on Tabular Data
Veronika Shilova, Abdoulaye Sakho, Younes Boumoussou +3
The paper proposes OT-FairBoost, an in-processing method that adds a Wasserstein-2 distance penalty to gradient-boosted tree training to improve group fairness while maintaining ac…
Distributional Limit Theory for Optimal Transport
Eustasio del Barrio, Alberto González-Sanz, Jean-Michel Loubes +1
The paper surveys recent theoretical results on the statistical behavior of empirical optimal transport quantities, such as plans, maps, and costs, and discusses how to construct c…
Exposing the Illusion of Fairness: Auditing Vulnerabilities to Distributional Manipulation Attacks
Valentin Lafargue, Adriana Laurindo Monteiro, Emmanuelle Claeys +2
The rapid deployment of AI systems in high-stakes domains, including those classified as high-risk under the The EU AI Act (Regulation (EU) 2024/1689), has intensified the need for…
Exact Functional ANOVA Decomposition for Categorical Inputs Models
Baptiste Ferrere, Nicolas Bousquet, Fabrice Gamboa +2
Functional ANOVA offers a principled framework for interpretability by decomposing a model's prediction into main effects and higher-order interactions. For independent features, t…
Minimax Private Estimation of Smooth Optimal-Transport Maps
Clément Lalanne, David RodrÃguez-VÃtores, Franck Iutzeler +1
We study the problem of estimating smooth optimal transport (OT) maps between two probability distributions under differential privacy (DP) constraints. Leveraging wavelet-based de…
Buzz, Choose, Forget: A Meta-Bandit Framework for Bee-Like Decision Making
Emmanuelle Claeys, Elena Kerjean, Jean-Michel Loubes
This work introduces MAYA, a sequential imitation learning model based on multi-armed bandits, designed to reproduce and predict individual bees' decisions in contextualized foragi…