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20242026
most citedDo we need rebalancing strategies? A theoretical and empirical study around SMOTE and its variants

4 citations · 4 across the 6 of their papers we have counts for

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stat.ML2026

Weighting-Based Strategies for Classification: Analysis and Local Peak Dynamics with CART Trees

Abdoulaye Sakho, Emmanuel Malherbe, Erwan Scornet

Tabular learning tasks often suffer from class imbalance, which is often addressed via weighting-based strategies. In this work, we compare the naive approach (unweighted) with the…

cs.LG2026

Better Capturing Interactions Between Products in~Retail: Revisited Negative Sampling for~Basket Choice Modeling

Jules Désir, Vincent Auriau, Martin Možina +1

Brick-and-mortar retailers face many different challenges that involve understanding thoroughly its products catalog and customer preferences. In particular, assortment optimizatio…

cs.AI2026

Weak Segmentation-Guided GAN for~Realistic Color Edition

Vincent Auriau, Emmanuel Malherbe, Matthieu Perrot

Editing the color of images in a realistic way finds many applications such as changing the perception of an image, data augmentation or film post processing. The design of an auto…

math.ST2026

OT-FairBoost: Optimal Transport-Guided Gradient Boosting for Fairness Regularization on Tabular Data

Veronika Shilova, Abdoulaye Sakho, Younes Boumoussou +3

Although neural-based machine learning models have received a lot of attention recently, tree-based models such as gradient boosting are competitive for tabular data and therefore…

cs.CV2026

Discovering Geometric Biases in 3D Face Reconstruction: A Curvature-Aware Spectral Framework for Fairness Evaluation

Veronika Shilova, Emmanuel Malherbe, Giovanni Palma +3

3D Morphable Models (3DMMs) remain the standard parametric shape priors for many state-of-the-art 3D face reconstruction algorithms. However, as these models are derived from a fin…

cs.AI2026

Identifying two piecewise linear additive value functions from anonymous preference information

Vincent Auriau, Khaled Belahcene, Emmanuel Malherbe +2

Eliciting a preference model involves asking a person, named decision-maker, a series of questions. We assume that these preferences can be represented by an additive value functio…