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This paper is concerned with an optimization problem that is constrained by the Kantorovich optimal transportation problem. This bilevel optimization problem can be reformulated as a mathematical problem with complementarity constraints in…

Optimization and Control · Mathematics 2022-11-15 Sebastian Hillbrecht , Paul Manns , Christian Meyer

We show that the Schroedinger equation is a lift of Newton's law of motion on the space of probability measures, where derivatives are taken w.r.t. the Wasserstein Riemannian metric. Here the potential is the sum of the total classical…

Mathematical Physics · Physics 2009-03-12 Max-K. von Renesse

Solutions to Monge-Kantorovich equations, expressing optimality condition in mass transportation problem with cost equal to distance, are stationary points of a critical-slope model for sand surface evolution. Using a dual variational…

Optimization and Control · Mathematics 2007-05-23 Leonid Prigozhin

This chapter describes techniques for the numerical resolution of optimal transport problems. We will consider several discretizations of these problems, and we will put a strong focus on the mathematical analysis of the algorithms to solve…

Numerical Analysis · Mathematics 2020-03-03 Quentin Merigot , Boris Thibert

The Sinkhorn--Knopp (SK) algorithm is a cornerstone method for matrix scaling and entropically regularized optimal transport (EOT). Despite its empirical efficiency, existing theoretical guarantees to achieve a target marginal accuracy…

Data Structures and Algorithms · Computer Science 2026-04-07 Kun He

We study generalizations of the Schr\"odinger problem in statistical mechanics in two directions: when the density is constrained at more than two times, and when the joint law of the initial and final positions for the particles is…

Probability · Mathematics 2020-01-30 Aymeric Baradat , Christian Léonard

We investigate the properties of convex functions in the plane that satisfy a local inequality which generalizes the notion of sub-solution of Monge-Ampere equation for a Monge-Kantorovich problem with quadratic cost between non-absolutely…

Analysis of PDEs · Mathematics 2021-04-08 P. -E. Jabin , A. Mellet , M. Molina

We develop a theory for image restoration with a learned regularizer that is analogous to that of Meyer's characterization of solutions of the classical variational method of Rudin-Osher-Fatemi (ROF). The learned regularizer we use is a…

Optimization and Control · Mathematics 2023-05-02 Tristan Milne , Adrian Nachman

We study the dual formulation of the Monge-Kantorovich optimal transportation problem, in particular under what circumstances it is permitted in an infinite dimensional setting to use cylindrical functions, i.e. functions of the form…

Functional Analysis · Mathematics 2015-04-13 Martijn Zaal

We give a new proof of the Caffarelli contraction theorem, which states that the Brenier optimal transport map sending the standard Gaussian measure onto a uniformly log-concave probability measure is Lipschitz. The proof combines a recent…

Probability · Mathematics 2019-04-15 Max Fathi , Nathael Gozlan , Maxime Prodhomme

We statistically analyze empirical plug-in estimators for unbalanced optimal transport (UOT) formalisms, focusing on the Kantorovich-Rubinstein distance, between general intensity measures based on observations from spatio-temporal point…

Statistics Theory · Mathematics 2025-09-05 Marina Struleva , Shayan Hundrieser , Dominic Schuhmacher , Axel Munk

We consider a class of stochastic optimal transport, SOT for short, with given two endpoint marginals in the case where a cost function exhibits at most quadratic growth. We first study the upper and lower estimates, the short--time…

Probability · Mathematics 2023-09-19 Toshio Mikami

For probability measures on countable spaces we derive distributional limits for empirical entropic optimal transport quantities. More precisely, we show that the empirical optimal transport plan weakly converges to a centered Gaussian…

Probability · Mathematics 2022-12-27 Shayan Hundrieser , Marcel Klatt , Axel Munk

We establish weak limits for the empirical entropy regularized optimal transport cost, the expectation of the empirical plan and the conditional expectation. Our results require only uniform boundedness of the cost function and no…

Statistics Theory · Mathematics 2023-05-18 Alberto González-Sanz , Shayan Hundrieser

We study solutions to the multi-marginal Monge-Kantorovich problem which are concentrated on several graphs over the first marginal. We first present two general conditions on the cost function which ensure, respectively, that any solution…

Optimization and Control · Mathematics 2015-07-22 Abbas Moameni , Brendan Pass

We consider an optimal transport problem between laws of random probability measures: given a base cost function, we build the associated OT cost between probability measures that in turn we use to define the OT cost between probability…

Optimization and Control · Mathematics 2026-05-05 Alessandro Pinzi

We study the regularity of optimal transport maps between convex domains with quadratic cost. For nondegenerate $C^{\alpha}$-densities, we prove $C^{1, 1-\varepsilon}$-regularity of the potentials up to the boundary. If in addition the…

Analysis of PDEs · Mathematics 2025-07-09 Tristan C. Collins , Freid Tong

In this paper, we study the multimarginal optimal transport with Coulomb cost, also known in the physics literature as the Strictly-Correlated Electrons (SCE) functional. We prove that the dual Kantorovich potential is an electrostatic…

Mathematical Physics · Physics 2022-09-01 Rodrigue Lelotte

We study the quadratically regularized optimal transport (QOT) problem for quadratic cost and compactly supported marginals $\mu$ and $\nu$. It has been empirically observed that the optimal coupling $\pi_\epsilon$ for the QOT problem has…

Optimization and Control · Mathematics 2024-10-07 Johannes Wiesel , Xingyu Xu

We study Sinkhorn's algorithm for solving the entropically regularized optimal transport problem. Its iterate $\pi_{t}$ is shown to satisfy $H(\pi_{t}|\pi_{*})+H(\pi_{*}|\pi_{t})=O(t^{-1})$ where $H$ denotes relative entropy and $\pi_{*}$…

Optimization and Control · Mathematics 2025-04-08 Promit Ghosal , Marcel Nutz