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20242026
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stat.ML2026

Fair regression under localized demographic parity constraints

Arthur Charpentier, Christophe Denis, Romuald Elie +2

Demographic parity (DP) is a widely used group fairness criterion requiring predictive distributions to be invariant across sensitive groups. While natural in classification, full…

stat.ML2026

Optimal Stopping in Latent Diffusion Models

Yu-Han Wu, Quentin Berthet, Gérard Biau +3

We identify and analyze a surprising phenomenon of Latent Diffusion Models (LDMs) where the final steps of the diffusion can degrade sample quality. In contrast to conventional arg…

stat.ML2026

Clustering in Deep Stochastic Transformers

Lev Fedorov, Michaël E. Sander, Romuald Elie +2

Transformers have revolutionized deep learning across various domains but understanding the precise token dynamics remains a theoretical challenge. Existing theories of deep Transf…

stat.ML2025

Dimension-free error estimate for diffusion model and optimal scheduling

Valentin de Bortoli, Romuald Elie, Anna Kazeykina +2

Diffusion generative models have emerged as powerful tools for producing synthetic data from an empirically observed distribution. A common approach involves simulating the time-re…

stat.ML2024

Fair Active Learning: Solving the Labeling Problem in Insurance

Romuald Elie, Caroline Hillairet, François Hu +1

This paper addresses significant obstacles that arise from the widespread use of machine learning models in the insurance industry, with a specific focus on promoting fairness. The…