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The calculation of transport profiles from experimental measurements belongs in the category of inverse problems which are known to come with issues of ill-conditioning or singularity. A reformulation of the calculation, the matricial…

Plasma Physics · Physics 2012-06-07 D. F. Escande , F. Sattin

The optimal transport problem studies how to transport one measure to another in the most cost-effective way and has wide range of applications from economics to machine learning. In this paper, we introduce and study an information…

Information Theory · Computer Science 2020-08-25 Yikun Bai , Xiugang Wu , Ayfer Ozgur

We consider the problem of optimal incomplete transportation between the empirical measure on an i.i.d. uniform sample on the d-dimensional unit cube $[0,1]^d$ and the true measure. This is a family of problems lying in between classical…

Probability · Mathematics 2013-10-04 Eustasio del Barrio , Carlos Matrán

Quantum functional inequalities (e.g. the logarithmic Sobolev- and Poincar\'e inequalities) have found widespread application in the study of the behavior of primitive quantum Markov semigroups. The classical counterparts of these…

Quantum Physics · Physics 2017-10-11 Cambyse Rouzé , Nilanjana Datta

Talagrand's inequalities make a link between two fundamentals concepts of probability: transport of measures and entropy. The study of the counterpart of these inequalities in the context of free probability has been initiated by Biane and…

Probability · Mathematics 2012-09-12 Mylène Maïda , Édouard Maurel-Segala

We consider Monge-Kantorovich optimal transport problems on $\mathbb{R}^d$, $d\ge 1$, with a convex cost function given by the cumulant generating function of a probability measure. Examples include the Wasserstein-2 transport whose cost…

Probability · Mathematics 2017-08-29 Soumik Pal

In this paper we provide a proof of the Sobolev-Poincar\'e inequality for variable exponent spaces by means of mass transportation methods. The importance of this approach is that the method is exible enough to deal with different…

Analysis of PDEs · Mathematics 2015-03-11 Juan Pablo Borthagaray , Julián Fernández Bonder , Analía Silva

We revisit several results on exponential integrability in probability spaces and derive some new ones. In particular, we give a quantitative form of recent results by Cianchi-Musil and Pick in the framework of Moser-Trudinger-type…

Probability · Mathematics 2023-12-19 Ali Barki , Sergey G. Bobkov , Esther Bou Dagher , Cyril Roberto

This paper develops a new divergence that generalizes relative entropy and can be used to compare probability measures without a requirement of absolute continuity. We establish properties of the divergence, and in particular derive and…

Probability · Mathematics 2019-11-19 Paul Dupuis , Yixiang Mao

We study the transportation problem on the unit sphere $S^{n-1}$ for symmetric probability measures and the cost function $c(x,y) = \log \frac{1}{\langle x, y \rangle}$. We calculate the variation of the corresponding Kantorovich functional…

Functional Analysis · Mathematics 2018-08-27 Alexander V. Kolesnikov

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 extend the duality theory of the multi-marginal optimal transport problem for cost functions depending on a decreasing function of the distance (not necessarily bounded). This class of cost functions appears in the context…

Analysis of PDEs · Mathematics 2018-05-03 Augusto Gerolin , Anna Kausamo , Tapio Rajala

We introduce a transport-majorization argument that establishes a majorization in the convex order between two densities, based on control of the gradient of a transportation map between them. As applications, we give elementary derivations…

Functional Analysis · Mathematics 2022-09-20 James Melbourne , Cyril Roberto

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

Who benefits from expanding transport networks? While designed to improve mobility, such interventions can also create inequality. In this paper, we show that disparities arise not only from the structure of the network itself but also from…

Computer Science and Game Theory · Computer Science 2026-02-02 Dimitris Michailidis , Sennay Ghebreab , Fernando P. Santos

In machine learning and computer vision, optimal transport has had significant success in learning generative models and defining metric distances between structured and stochastic data objects, that can be cast as probability measures. The…

Machine Learning · Computer Science 2020-10-20 Anton Mallasto , Markus Heinonen , Samuel Kaski

This paper introduces a mobility equity metric (MEM) for evaluating fairness and accessibility in multi-modal intelligent transportation systems. The MEM simultaneously accounts for service accessibility and transportation costs across…

Systems and Control · Electrical Eng. & Systems 2025-04-08 Heeseung Bang , Aditya Dave , Filippos N. Tzortzoglou , Shanting Wang , Andreas A. Malikopoulos

We prove that the laws of the BPHZ random models satisfy some transportation cost inequalities in the full subcritical regime if there is no 'variance blowup' and the law of the noise is translation invariant and satisfies some…

Probability · Mathematics 2026-03-27 I. Bailleul , M. Hoshino , R. Takano

In many areas of engineering and sciences, decision rules and control strategies are usually designed based on nominal values of relevant system parameters. To ensure that a control strategy or decision rule will work properly when the…

Probability · Mathematics 2020-06-16 Xinjia Chen

We study the sample complexity of entropic optimal transport in high dimensions using computationally efficient plug-in estimators. We significantly advance the state of the art by establishing dimension-free, parametric rates for…

Statistics Theory · Mathematics 2022-06-28 Philippe Rigollet , Austin J. Stromme
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