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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

In this article we show how ideas, methods and results from optimal transportation can be used to study various aspects of the stationary measuresof Iterated Function Systems equipped with a probability distribution. We recover a classical…

Classical Analysis and ODEs · Mathematics 2021-06-02 Benoît Kloeckner

Several extensions of the classical optimal transport distances to the quantum setting have been proposed. In this paper, we investigate the pseudometrics introduced by Golse, Mouhot and Paul in [Commun Math Phys 343:165-205, 2016] and by…

Analysis of PDEs · Mathematics 2023-12-25 Laurent Lafleche

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 show that, on a $2$-dimensional compact manifold, the optimal transport map in the semi-discrete random matching problem is well-approximated in the $L^2$-norm by identity plus the gradient of the solution to the Poisson problem $-\Delta…

Probability · Mathematics 2019-03-29 Luigi Ambrosio , Federico Glaudo , Dario Trevisan

The scope of this note is to make a self-contained survey of the recent developments and achievements of the theory of L1-Optimal Transportation on metric measure spaces. Among the results proved in the recent papers [20, 21] where the…

Metric Geometry · Mathematics 2018-09-14 Fabio Cavalletti

We present a new approach to Bayesian inference that entirely avoids Markov chain simulation, by constructing a map that pushes forward the prior measure to the posterior measure. Existence and uniqueness of a suitable measure-preserving…

Computation · Statistics 2012-08-31 Tarek A. El Moselhy , Youssef M. Marzouk

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

Loosely speaking, causal transport plans are a relaxation of adapted processes in the same sense as Kantorovich transport plans extend Monge-type transport maps. The corresponding causal version of the transport problem has recently been…

Optimization and Control · Mathematics 2017-03-24 Julio Backhoff Veraguas , Mathias Beiglböck , Yiqing Lin , Anastasiia Zalashko

We present a general convex relaxation approach to study a wide class of Unbalanced Optimal Transport problems for finite non-negative measures with possibly different masses. These are obtained as the lower semicontinuous and convex…

Optimization and Control · Mathematics 2024-01-02 Giuseppe Savaré , Giacomo Enrico Sodini

We consider discrete metric spaces and we look for non-constant contractions. We introduce the notion of contractive map and we characterize the spaces with non-constant contractive maps. We provide some examples to discussion the possible…

Classical Analysis and ODEs · Mathematics 2010-11-19 Fabio Zucca

We prove new concentration estimates for random variables that are functionals of a Poisson measure defined on a general measure space. Our results are specifically adapted to geometric applications, and are based on a pervasive use of a…

Probability · Mathematics 2015-04-14 Sascha Bachmann , Giovanni Peccati

We show that the modified log-Sobolev constant for a natural Markov chain which converges to an $r$-homogeneous strongly log-concave distribution is at least $1/r$. Applications include a sharp mixing time bound for the bases-exchange walk…

Probability · Mathematics 2020-08-11 Mary Cryan , Heng Guo , Giorgos Mousa

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 establish numerical methods for solving the martingale optimal transport problem (MOT) - a version of the classical optimal transport with an additional martingale constraint on transport's dynamics. We prove that the MOT value can be…

Probability · Mathematics 2019-04-08 Gaoyue Guo , Jan Obloj

We propose a new discretization of the mirror-Langevin diffusion and give a crisp proof of its convergence. Our analysis uses relative convexity/smoothness and self-concordance, ideas which originated in convex optimization, together with a…

Statistics Theory · Mathematics 2021-10-26 Kwangjun Ahn , Sinho Chewi

We explore alternative functional or transport-entropy formulations of the Blaschke-Santal{\'o} inequality and of its conjectured counterpart due to Mahler. In particular, we obtain new direct and reverse Blaschke-Santal{\'o} inequalities…

Functional Analysis · Mathematics 2023-07-11 Matthieu Fradelizi , Nathael Gozlan , Shay Sadovsky , Simon Zugmeyer

We employ techniques from optimal transport in order to prove decay of transfer operators associated to iterated functions systems and expanding maps, giving rise to a new proof without requiring a Doeblin-Fortet (or Lasota-Yorke)…

Dynamical Systems · Mathematics 2015-08-25 Benoit Kloeckner , Artur Lopes , Manuel Stadlbauer

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 Poisson or a binomial process on an abstract state space and a symmetric function $f$ acting on $k$-tuples of its points are considered. They induce a point process on the target space of $f$. The main result is a functional limit theorem…

Probability · Mathematics 2016-06-07 Laurent Decreusefond , Matthias Schulte , Christoph Thäle