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Related papers: The Monge-Kantorovich problem on Wasserstein space

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Optimal transportation theory and the related $p$-Wasserstein distance ($W_p$, $p\geq 1$) are widely-applied in statistics and machine learning. In spite of their popularity, inference based on these tools has some issues. For instance, it…

Statistics Theory · Mathematics 2024-03-01 Yiming Ma , Hang Liu , Davide La Vecchia , Metthieu Lerasle

In the classical Monge-Kantorovich problem, the transportation cost only depends on the amount of mass sent from sources to destinations and not on the paths followed by this mass. Thus, it does not allow for congestion effects. Using the…

Optimization and Control · Mathematics 2007-05-23 G. Carlier , C. Jimenez , F. Santambrogio

We investigate the problem of pairwise multi-marginal optimal transport, that is, given a collection of probability distributions $\{P_\alpha\}$ on a Polish space $\mathcal{X}$, to find a coupling $\{X_\alpha\}$, $X_\alpha\sim P_\alpha$,…

Probability · Mathematics 2019-10-22 Cheuk Ting Li , Venkat Anantharam

We analyze a number of natural estimators for the optimal transport map between two distributions and show that they are minimax optimal. We adopt the plugin approach: our estimators are simply optimal couplings between measures derived…

Statistics Theory · Mathematics 2024-06-18 Tudor Manole , Sivaraman Balakrishnan , Jonathan Niles-Weed , Larry Wasserman

Let $X$ be a Polish space, $\mathcal{P}(X)$ be the set of Borel probability measures on $X$, and $T\colon X\to X$ be a homeomorphism. We prove that for the simplex $\mathrm{Dom} \subseteq \mathcal{P}(X)$ of all $T$-invariant measures, the…

Probability · Mathematics 2015-11-05 Danila Zaev

Computing optimal transport (OT) between measures in high dimensions is doomed by the curse of dimensionality. A popular approach to avoid this curse is to project input measures on lower-dimensional subspaces (1D lines in the case of…

Machine Learning · Computer Science 2019-10-30 Boris Muzellec , Marco Cuturi

We establish several quantitative stability estimates for optimal transport maps between non-degenerate densities on uniformly convex domains for the quadratic cost. Under H\"older regularity assumptions, we prove Lipschitz $L^2$…

Analysis of PDEs · Mathematics 2026-05-26 F. -U. Caja-Lopez , Matias G. Delgadino , Jun Kitagawa

We introduce the optimal transportation interpretation of the Kantorovich norm on thespace of signed Radon measures with finite mass, based on a generalized Wasserstein distancefor measures with different masses.With the formulation and the…

Analysis of PDEs · Mathematics 2019-10-14 Benedetto Piccoli , Francesco Rossi , Magali Tournus

We study the problem of minimizing the Wasserstein distance between a probability distribution and an algebraic variety. We consider the setting of finite state spaces and describe the solution depending on the choice of the ground metric…

Optimization and Control · Mathematics 2020-01-15 T. Ö. Çelik , A. Jamneshan , G. Montúfar , B. Sturmfels , L. Venturello

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

We introduce a novel optimal transport framework for probabilistic circuits (PCs). While it has been shown recently that divergences between distributions represented as certain classes of PCs can be computed tractably, to the best of our…

Artificial Intelligence · Computer Science 2025-10-16 Adrian Ciotinga , YooJung Choi

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

We develop a full theory for the new class of Optimal Entropy-Transport problems between nonnegative and finite Radon measures in general topological spaces. They arise quite naturally by relaxing the marginal constraints typical of Optimal…

Optimization and Control · Mathematics 2018-10-16 Matthias Liero , Alexander Mielke , Giuseppe Savaré

The paper proves transportation inequalities for probability measures on spheres for the Wasserstein metrics with respect to cost functions that are powers of the geodesic distance. Let $\mu$ be a probability measure on the sphere ${\bf…

Probability · Mathematics 2024-09-24 Gordon Blower

We consider an extension of the Monge-Kantorovitch optimal transportation problem. The mass is transported along a continuous semimartingale, and the cost of transportation depends on the drift and the diffusion coefficients of the…

Probability · Mathematics 2013-10-04 Xiaolu Tan , Nizar Touzi

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

In recent work arXiv:2109.07820 we have shown the equivalence of the widely used nonconvex (generalized) branched transport problem with a shape optimization problem of a street or railroad network, known as (generalized) urban planning…

Optimization and Control · Mathematics 2022-10-19 Julius Lohmann , Bernhard Schmitzer , Benedikt Wirth

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

This article presents a new class of distances between arbitrary nonnegative Radon measures inspired by optimal transport. These distances are defined by two equivalent alternative formulations: (i) a dynamic formulation defining the…

Optimization and Control · Mathematics 2019-02-12 Lenaic Chizat , Gabriel Peyré , Bernhard Schmitzer , François-Xavier Vialard

Since the introduction of the Sliced Wasserstein distance in the literature, its simplicity and efficiency have made it one of the most interesting surrogate for the Wasserstein distance in image processing and machine learning. However,…

Optimization and Control · Mathematics 2025-08-05 Eloi Tanguy , Laetitia Chapel , Julie Delon
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