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This paper studies the uniqueness of solutions to the dual optimal transport problem, both qualitatively and quantitatively (bounds on the diameter of the set of optimisers). On the qualitative side, we prove that when one marginal…

Optimization and Control · Mathematics 2026-04-03 William Ford

We establish novel quantitative stability results for optimal transport problems with respect to perturbations in the target measure. We provide explicit bounds on the stability of optimal transport potentials and maps, which are relevant…

Functional Analysis · Mathematics 2026-05-12 Octave Mischler , Dario Trevisan

We study the stability of entropically regularized optimal transport with respect to the marginals. Lipschitz continuity of the value and H\"older continuity of the optimal coupling in $p$-Wasserstein distance are obtained under general…

Optimization and Control · Mathematics 2022-07-06 Stephan Eckstein , Marcel Nutz

Quadratically regularized optimal transport (QOT) is a sparse alternative to entropic optimal transport. We develop a quantitative stability theory for QOT under perturbations of the marginals, the transport cost function, and the…

Optimization and Control · Mathematics 2026-05-28 Alberto González-Sanz , Marcel Nutz

We study the quantitative stability of the mapping that to a measure associates its pushforward measure by a fixed (non-smooth) optimal transport map. We exhibit a tight H\"older-behavior for this operation under minimal assumptions. Our…

Optimization and Control · Mathematics 2024-01-08 Guillaume Carlier , Alex Delalande , Quentin Mérigot

We prove quantitative bounds on the stability of optimal transport maps and Kantorovich potentials from a fixed source measure $\rho$ under variations of the target measure $\mu$, when the cost function is the squared Riemannian distance on…

Metric Geometry · Mathematics 2025-05-06 Jun Kitagawa , Cyril Letrouit , Quentin Mérigot

The Monge-Kantorovich problem for the infinite Wasserstein distance presents several peculiarities. Among them the lack of convexity and then of a direct duality. We study in dimension 1 the dual problem introduced by Barron, Bocea and…

Optimization and Control · Mathematics 2017-08-08 Luigi De Pascale , Jean Louet

We study stability and sample complexity properties of divergence regularized optimal transport (DOT). First, we obtain quantitative stability results for optimizers of DOT measured in Wasserstein distance, which are applicable to a wide…

Optimization and Control · Mathematics 2024-01-17 Erhan Bayraktar , Stephan Eckstein , Xin Zhang

We use a Korevaar-style maximum principle approach to show the following: Fixing a $C^{2}$ bound on the log densities of a set of smooth measures, there is a quantifiably-sized Wasserstein neighborhood over which all pairs of such measures…

Analysis of PDEs · Mathematics 2025-07-15 Micah Warren

We analyze optimal transport problems with additional entropic cost evaluated along curves in the Wasserstein space which join two probability measures $m_0,m_1$. The effect of the additional entropy functional results into an elliptic…

Analysis of PDEs · Mathematics 2022-11-18 Alessio Porretta

In this paper, we prove a structure theorem for discrete optimal transportation plans. We show that, given any pair of discrete probability measures and a cost function, there exists an optimal transportation plan that can be expressed as…

Optimization and Control · Mathematics 2021-04-28 Gennaro Auricchio , Marco Veneroni

This work studies the quantitative stability of the quadratic optimal transport map between a fixed probability density $\rho$ and a probability measure $\mu$ on R^d , which we denote T$\mu$. Assuming that the source density $\rho$ is…

Functional Analysis · Mathematics 2023-03-09 Alex Delalande , Quentin Merigot

We introduce folded optimal transport, as a method to extend a cost or distance defined on the extreme boundary of a convex to the whole convex, related to convex extension. This construction broadens the framework of standard optimal…

Functional Analysis · Mathematics 2026-01-21 Thomas Borsoni

The classical problem of optimal transportation can be formulated as a linear optimization problem on a convex domain: among all joint measures with fixed marginals find the optimal one, where optimality is measured against a cost function.…

Optimization and Control · Mathematics 2012-11-29 Jonathan Korman , Robert J. McCann

We show quantitative stability results for the geometric "cells" arising in semi-discrete optimal transport problems. Our results show two types of stability, the first is stability of the associated Laguerre cells in measure, without any…

Analysis of PDEs · Mathematics 2021-02-11 Mohit Bansil , Jun Kitagawa

The Cauchy problem for a multidimensional linear transport equation with discontinuous coefficient is investigated. Provided the coefficient satisfies a one-sided Lipschitz condition, existence, uniqueness and weak stability of solutions…

Analysis of PDEs · Mathematics 2007-05-23 Francois James , Simona Mancini , Francois Bouchut

This paper focuses on martingale optimal transport problems when the martingales are assumed to have bounded quadratic variation. First, we give a result that characterizes the existence of a probability measure satisfying some convex…

Probability · Mathematics 2020-03-18 Erhan Bayraktar , Xin Zhang , Zhou Zhou

Stability of the value function and the set of minimizers w.r.t. the given data is a desirable feature of optimal transport problems. For the classical Kantorovich transport problem, stability is satisfied under mild assumptions and in…

Optimization and Control · Mathematics 2021-01-19 Martin Brückerhoff , Nicolas Juillet

We shall present a measure theoretical approach for which together with the Kantorovich duality provide an efficient tool to study the optimal transport problem. Specifically, we study the support of optimal plans where the cost function…

Analysis of PDEs · Mathematics 2014-11-21 Abbas Moameni

Semi-discrete optimal transport problems, which evaluate the Wasserstein distance between a discrete and a generic (possibly non-discrete) probability measure, are believed to be computationally hard. Even though such problems are…

Machine Learning · Computer Science 2022-05-02 Bahar Taskesen , Soroosh Shafieezadeh-Abadeh , Daniel Kuhn
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