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The stability of solutions to optimal transport problems under variation of the measures is fundamental from a mathematical viewpoint: it is closely related to the convergence of numerical approaches to solve optimal transport problems and…

Numerical Analysis · Mathematics 2022-07-25 Anatole Gallouët , Quentin Mérigot , Boris Thibert

We consider the Monge-Kantorovich transport problem in a purely measure theoretic setting, i.e. without imposing continuity assumptions on the cost function. It is known that transport plans which are concentrated on c-monotone sets are…

Optimization and Control · Mathematics 2009-01-19 Mathias Beiglböck , Martin Goldstern , Gabriel Maresch , Walter Schachermayer

In this note, we present a unified approach to the problem of existence of a potential for the optimal transport problem with respect to non-traditional cost functions, that is, costs that assume infinite values. We establish a new method…

Metric Geometry · Mathematics 2025-03-04 Shiri Artstein-Avidan , Shay Sadovsky , Katarzyna Wyczesany

In this short note, we show that given a cost function $c$, any coupling $\pi$ of two probability measures where the second is a discrete measure can be associated to a certain bipartite graph containing a perfect matching, based on the…

Optimization and Control · Mathematics 2020-07-17 Mohit Bansil , Jun Kitagawa

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

This paper slightly improves a classical result by Gangbo and McCann (1996) about the structure of optimal transport plans for costs that are concave functions of the Euclidean distance. Since the main difficulty for proving the existence…

Optimization and Control · Mathematics 2025-09-03 Paul Pegon , Davide Piazzoli , Filippo Santambrogio

We consider the Monge problem of optimal transport between a compactly supported source measure and a target probability measure with unbounded support. We consider the convergence of optimal maps and potential functions when the target…

Numerical Analysis · Mathematics 2026-03-03 Axel G. R. Turnquist

This article generalizes the study of ramified optimal transport with capacity constraint in transport multi-paths by generalizing the $\mathbf{M}_{\alpha}$ cost to $\mathbf{M}_{\alpha,c}$, which incorporates capacity constraints into the…

Optimization and Control · Mathematics 2025-10-14 Qinglan Xia , Haotian Sun

We consider optimal transportation of measures on metric and topological spaces in the case where the cost function and marginal distributions depend on a parameter with values in a metric space. The Hausdorff distance between the sets of…

Functional Analysis · Mathematics 2021-11-29 Vladimir Bogachev , Svetlana Popova

We consider the optimal mass transportation problem in $\RR^d$ with measurably parameterized marginals, for general cost functions and under conditions ensuring the existence of a unique optimal transport map. We prove a joint measurability…

Probability · Mathematics 2008-09-09 Joaquin Fontbona , Helene Guerin , Sylvie Meleard

This paper studies the geometry of the optimizer for the optimal transport problem with capacity constraints. We introduce the concept of c-capacity monotonicity, which is a generalization of c-cyclical monotonicity in optimal transport. We…

Optimization and Control · Mathematics 2025-11-03 Dongwei Chen

Optimal maps, solutions to the optimal transportation problems, are completely determined by the corresponding c-convex potential functions. In this paper, we give simple sufficient conditions for a smooth function to be c-convex when the…

Differential Geometry · Mathematics 2010-06-22 Paul W. Y. Lee

We identify a condition for regularity of optimal transport maps that requires only three derivatives of the cost function, for measures given by densities that are only bounded above and below. This new condition is equivalent to the weak…

Analysis of PDEs · Mathematics 2013-01-25 Nestor Guillen , Jun Kitagawa

The duality theory of the Monge-Kantorovich transport problem is investigated in an abstract measure theoretic framework. Let $(\mathcal{X},\mathcal{F},\mu)$ and $(\mathcal{Y},\mathcal{G},\nu)$ be any probability spaces and…

Probability · Mathematics 2019-07-17 Pietro Rigo

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

We show that in any complete metric space the probability measures $\mu$ with compact and connected support are the ones having the property that the optimal tranportation distance to any other probability measure $\nu$ living on the…

Analysis of PDEs · Mathematics 2015-08-24 Heikki Jylhä , Tapio Rajala

$c$-cyclical monotonicity is the most important optimality condition for an optimal transport plan. While the proof of necessity is relatively easy, the proof of sufficiency is often more difficult or even elusive. We present here a new…

Optimization and Control · Mathematics 2022-12-19 Luigi De Pascale , Anna Kausamo

This article generalizes the study of branched/ramified optimal transportation to those with capacity constraints. Each admissible transport network studied here is represented by a transport multi-path between measures, with a capacity…

Optimization and Control · Mathematics 2024-02-13 Qinglan Xia , Haotian Sun

In this thesis, the main objects of study are probability measures on the isomorphism classes of countable, connected rooted graphs. An important class of such measures is formed by unimodular measures, which satisfy a certain equation,…

Combinatorics · Mathematics 2014-01-29 Igor Artemenko

Coupling probability measures lies at the core of many problems in statistics and machine learning, from domain adaptation to transfer learning and causal inference. Yet, even when restricted to deterministic transports, such couplings are…

Machine Learning · Statistics 2025-09-22 Lucas De Lara , Luca Ganassali
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