Entropic vector quantile regression: Duality and Gaussian case

Fuente: arXiv
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Hauptverfasser: Kato, Kengo, Wang, Boyu
Format: Preprint
Veröffentlicht: 2026
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author Kato, Kengo
Wang, Boyu
author_facet Kato, Kengo
Wang, Boyu
contents Vector quantile regression (VQR) is an optimal transport (OT) problem subject to a mean-independence constraint that extends classical linear quantile regression to vector response variables. Motivated by computational considerations, prior work has considered entropic relaxation of VQR, but its fundamental structural and approximation properties are still much less understood than entropic OT. The goal of this paper is to address some of these gaps. First, we study duality theory for entropic VQR and establish strong duality and dual attainment for marginals with possibly unbounded supports. In addition, when all marginals are compactly supported, we show that dual potentials are real analytic. Second, building on our duality theory, when all marginals are Gaussian, we show that entropic VQR has a closed-form optimal solution, which is again Gaussian, and establish the precise approximation rate toward unregularized VQR.
format Preprint
id arxiv_https___arxiv_org_abs_2602_11290
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Entropic vector quantile regression: Duality and Gaussian case
Kato, Kengo
Wang, Boyu
Statistics Theory
Optimization and Control
Vector quantile regression (VQR) is an optimal transport (OT) problem subject to a mean-independence constraint that extends classical linear quantile regression to vector response variables. Motivated by computational considerations, prior work has considered entropic relaxation of VQR, but its fundamental structural and approximation properties are still much less understood than entropic OT. The goal of this paper is to address some of these gaps. First, we study duality theory for entropic VQR and establish strong duality and dual attainment for marginals with possibly unbounded supports. In addition, when all marginals are compactly supported, we show that dual potentials are real analytic. Second, building on our duality theory, when all marginals are Gaussian, we show that entropic VQR has a closed-form optimal solution, which is again Gaussian, and establish the precise approximation rate toward unregularized VQR.
title Entropic vector quantile regression: Duality and Gaussian case
topic Statistics Theory
Optimization and Control
url https://arxiv.org/abs/2602.11290