Séminaire Jeunes chercheurs (Aminata Ndiaye, jeudi 16 octobre 2025)

La prochaine séance du séminaire Jeunes chercheurs du CEREMADE aura lieu le jeudi 16 octobre 2025 à 17h en salle A707. Nous aurons le plaisir d'écouter Aminata Ndiaye (Ceremade), qui nous parlera de

Marginal contrastive discrimination for conditional density estimation

Abstract
Conditional density estimation is a central problem in statistics and machine learning, particularly when the target variable Y is univariate but the conditioning set X is high dimensional. Traditional methods often struggle in this regime due to the curse of dimensionality. We propose Marginal Contrastive Discrimination (MCD ), a novel approach that reformulates conditional density estimation as a combination of marginal density estimation and binary classification. The key idea is to construct a contrastive training dataset by mixing true pairs (X, Y) with independent samples, allowing for controlled joint–marginal mixtures. This framework naturally extends to settings with additional marginal data or multiple targets per observation, enabling principled dataset enlargement while preserving theoretical guarantees. Experiments demonstrate that MCD achieves performance comparable to, and sometimes exceeding, state-of-the-art conditional density estimators, particularly in high-dimensional conditioning spaces.