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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

In this work we study a modification of the Monge-Kantorovich problem taking into account path dependence and interaction effects between particles. We prove existence of solutions under mild conditions on the data, and after imposing…

Analysis of PDEs · Mathematics 2022-04-19 Rene Cabrera

The theory of Monge-Kantorovich Optimal Mass Transport (OMT) has in recent years spurred a fast developing phase of research in stochastic control, control of ensemble systems, thermodynamics, data science, and several other fields in…

Optimization and Control · Mathematics 2025-08-14 Mahmoud Abdelgalil , Tryphon T. Georgiou

Let $L$ be a convex cone of real random variables on the probability space $(\Omega,\mathcal{A},P_0)$. The existence of a probability $P$ on $\mathcal{A}$ such that $$ P \sim P_0,\quad E_P \abs{X}< \infty\, \text{ and } \, E_P(X) \leq 0\,…

Probability · Mathematics 2014-02-17 Patrizia Berti , Luca Pratelli , Pietro Rigo

Optimal transportation problem seeks for a coupling $\pi$ of two probability measures $\mu$ and $\nu$ which minimize the total cost $\int c d\pi$, which is linear in $\pi$. In this paper, we introduce a variation of optimal transportation…

Optimization and Control · Mathematics 2025-02-06 Seonghyeon Jeong

Optimal Transport is a foundational mathematical theory that connects optimization, partial differential equations, and probability. It offers a powerful framework for comparing probability distributions and has recently become an important…

Machine Learning · Statistics 2025-05-13 Gabriel Peyré

We propose a discrete time formulation of the semi martingale optimal transport problembased on multi-marginal entropic transport. This approach offers a new way to formulate and solve numerically the calibration problem proposed by Guo et…

Optimization and Control · Mathematics 2024-06-18 Jean-David Benamou , Guillaume Chazareix , Grégoire Loeper

We establish dual attainment for the multimarginal, multi-asset martingale optimal transport (MOT) problem, a fundamental question in the mathematical theory of model-independent pricing and hedging in quantitative finance. Our main result…

Mathematical Finance · Quantitative Finance 2026-02-04 Charlie Che , Tongseok Lim , Yue Sun

We provide a compactness criterion for the set of laws $\mathfrak{P}^{ac}_{sem}(\Theta)$ on the Skorokhod space for which the canonical process $X$ is a semimartingale having absolutely continuous characteristics with differential…

Probability · Mathematics 2018-05-11 Chong Liu , Ariel Neufeld

This work is devoted to direct mass transportation proofs of families of functional inequalities in the context of one-dimensional free probability, avoiding random matrix approximation. The inequalities include the free form of the…

Functional Analysis · Mathematics 2009-03-24 Michel Ledoux , Ionel Popescu

We consider the Monge-Kantorovich transport problem in an abstract measure theoretic setting. Our main result states that duality holds if $c:X\times Y\to [0,\infty)$ is an arbitrary Borel measurable cost function on the product of Polish…

Optimization and Control · Mathematics 2008-07-10 Mathias Beiglböck , Walter Schachermayer

Optimal transport has become part of the standard quantitative economics toolbox. It is the framework of choice to describe models of matching with transfers, but beyond that, it allows to: extend quantile regression; identify discrete…

General Economics · Economics 2021-07-13 Alfred Galichon

We provide a unifying interpretation of various optimal transport problems as a minimisation of a linear functional over the set of all Choquet representations of a given pair of probability measures ordered with respect to a certain convex…

Functional Analysis · Mathematics 2023-03-06 Krzysztof J. Ciosmak

A convex duality result for martingale optimal transport problems with two marginals was established in Beiglb\"ock et al. (2013). In this paper we provide a generalization of this result to the multi-period setting.

Probability · Mathematics 2024-03-06 Julian Sester

The Optimal transport (OT) problem is rapidly finding its way into machine learning. Favoring its use are its metric properties. Many problems admit solutions with guarantees only for objects embedded in metric spaces, and the use of…

Machine Learning · Computer Science 2022-12-26 Liang Mi , Azadeh Sheikholeslami , José Bento

This paper investigates causal optimal transportation problems, in the framework of two Polish spaces, both endowed with filtrations. Specific concretizations yield primal problems equivalent to several classical problems of stochastic…

Probability · Mathematics 2015-10-05 Rémi Lassalle

We consider the multidimensional Monge-Kantrovich transport problem in an abstract setting. Our main results state that if a cost function and marginal measures are invariant by a family of transformations, then a solution of the Kantrovich…

Analysis of PDEs · Mathematics 2015-04-22 Abbas Moameni

It is known that the Azema-Yor solution to the Skorokhod embedding problem maximizes the law of the running maximum of an uniformly integrable martingale with given terminal value distribution. Recently this optimality property has been…

Probability · Mathematics 2015-12-14 Nikolay Lysenko

A prominent model for transportation networks is branched transport, which seeks the optimal transportation scheme to move material from a given initial to a final distribution. The cost of the scheme encodes a higher transport efficiency…

Classical Analysis and ODEs · Mathematics 2020-09-04 Alessio Brancolini , Benedikt Wirth

We present a new ansatz space for the general symmetric multi-marginal Kantorovich optimal transport problem on finite state spaces which reduces the number of unknowns from $\tbinom{N+\ell-1}{\ell-1}$ to $\ell\cdot(N+1)$, where $\ell$ is…

Analysis of PDEs · Mathematics 2018-01-03 G. Friesecke , D. Vögler