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This paper deals with the existence of optimal transport maps for some optimal transport problems with a convex but non strictly convex cost. We give a decomposition strategy to address this issue. As part of our strategy, we have to treat…

Classical Analysis and ODEs · Mathematics 2009-09-16 Guillaume Carlier , Luigi De Pascale , Filippo Santambrogio

This paper presents a novel two-step approach for the fundamental problem of learning an optimal map from one distribution to another. First, we learn an optimal transport (OT) plan, which can be thought as a one-to-many map between the two…

A probabilistic method for solving the Monge-Kantorovich mass transport problem on $R^d$ is introduced. A system of empirical measures of independent particles is built in such a way that it obeys a doubly indexed large deviation principle…

Probability · Mathematics 2007-10-09 Christian Léonard

Continuity of the value of the martingale optimal transport problem on the real line w.r.t. its marginals was recently established in Backhoff-Veraguas and Pammer [2] and Wiesel [21]. We present a new perspective of this result using the…

Probability · Mathematics 2021-04-23 Ariel Neufeld , Julian Sester

We consider maps which preserve functions which are built out of the invariants of some simple vector fields. We give a reduction procedure, which can be used to derive commuting maps of the plane, which preserve the same symplectic form…

Mathematical Physics · Physics 2013-07-02 Allan P Fordy , Pavlos Kassotakis

The need to reason about uncertainty in large, complex, and multi-modal datasets has become increasingly common across modern scientific environments. The ability to transform samples from one distribution $P$ to another distribution $Q$…

Machine Learning · Statistics 2018-11-30 Diego A. Mesa , Justin Tantiongloc , Marcela Mendoza , Todd P. Coleman

In this paper, we present a novel and principled approach to learn the optimal transport between two distributions, from samples. Guided by the optimal transport theory, we learn the optimal Kantorovich potential which induces the optimal…

Machine Learning · Computer Science 2020-06-19 Ashok Vardhan Makkuva , Amirhossein Taghvaei , Sewoong Oh , Jason D. Lee

For a morphism $f : X \to Y$ of schemes, we give a tropical criterion for which points of $Y$ (valued in a field, discrete valuation ring, number ring, or Dedekind domain) lift to $X$. Our criterion extends the firmaments of Abramovich to a…

Algebraic Geometry · Mathematics 2025-09-16 Leo Herr , Sara Mehidi , Marta Pieropan , Thibault Poiret

We propose a volumetric formulation for computing the Optimal Transport problem defined on surfaces in $\mathbb{R}^3$, found in disciplines like optics, computer graphics, and computational methodologies. Instead of directly tackling the…

Numerical Analysis · Mathematics 2024-05-16 Richard Tsai , Axel G. R. Turnquist

We study the entropic regularizations of optimal transport problems under suitable summability assumptions on the point-wise transport cost. These summability assumptions already appear in the literature. However, we show that the weakest…

Optimization and Control · Mathematics 2025-12-30 Camilla Brizzi , Luigi De Pascale , Anna Kausamo

This paper presents a multiscale approach to efficiently compute approximate optimal transport plans between point sets. It is particularly well-suited for point sets that are in high-dimensions, but are close to being intrinsically…

Machine Learning · Computer Science 2021-04-13 Samuel Gerber , Mauro Maggioni

A variant of the classical optimal transportation problem is: among all joint measures with fixed marginals and which are dominated by a given density, find the optimal one. Existence and uniqueness of solutions to this variant were…

Optimization and Control · Mathematics 2018-01-23 Jonathan Korman , Robert J. McCann

This paper presents a selected tour through the theory and applications of lifts of convex sets. A lift of a convex set is a higher-dimensional convex set that projects onto the original set. Many convex sets have lifts that are…

Optimization and Control · Mathematics 2023-03-24 Hamza Fawzi , João Gouveia , Pablo A. Parrilo , James Saunderson , Rekha R. Thomas

For $0<p<+\infty$, we prove a global $W^{2,p}$-estimate for potentials of optimal transport maps between convex domains in the plane. Among the tools developed for that purpose are obliqueness in general convex domains and estimates for the…

Analysis of PDEs · Mathematics 2020-12-16 Ovidiu Savin , Hui Yu

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

A convex envelope for the problem of finding the best approximation to a given matrix with a prescribed rank is constructed. This convex envelope allows the usage of traditional optimization techniques when additional constraints are added…

Functional Analysis · Mathematics 2016-08-30 Fredrik Andersson , Marcus Carlsson , Carl Olsson

A function is exponentially concave if its exponential is concave. We consider exponentially concave functions on the unit simplex. In a previous paper we showed that gradient maps of exponentially concave functions provide solutions to a…

Probability · Mathematics 2017-06-01 Soumik Pal , Ting-Kam Leonard Wong

We characterize those regular, holomorphic or formal maps into the orbit space $V/G$ of a complex representation of a finite group $G$ which admit a regular, holomorphic or formal lift to the representation space $V$. In particular, the…

Algebraic Geometry · Mathematics 2008-05-05 Andreas Kriegl , Mark Losik , Peter W. Michor , Armin Rainer

There are interesting extensions of the problem of determining a joint probability with known marginals. On the one hand, one may impose size constraints on the joint probabilities. On the other, one may impose additional constraints like…

Probability · Mathematics 2021-09-08 Henryk Gzyl

We study multi-marginal optimal transport problems from a probabilistic graphical model perspective. We point out an elegant connection between the two when the underlying cost for optimal transport allows a graph structure. In particular,…

Optimization and Control · Mathematics 2020-06-26 Isabel Haasler , Rahul Singh , Qinsheng Zhang , Johan Karlsson , Yongxin Chen