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We study first-order optimality conditions for constrained optimization in the Wasserstein space, whereby one seeks to minimize a real-valued function over the space of probability measures endowed with the Wasserstein distance. Our…

Optimization and Control · Mathematics 2025-03-03 Nicolas Lanzetti , Saverio Bolognani , Florian Dörfler

We study the convergence of divergence-regularized optimal transport as the regularization parameter vanishes. Sharp rates for general divergences including relative entropy or $L^{p}$ regularization, general transport costs and…

Optimization and Control · Mathematics 2023-06-22 Stephan Eckstein , Marcel Nutz

Kantorovich distance (or 1-Wasserstein distance) on the probability simplex of a finite metric space is the value of a Linear Programming problem for which a closed-form expression is known in some cases. When the ground distance is defined…

Probability · Mathematics 2019-11-12 Luigi Montrucchio , Giovanni Pistone

An easy consequence of Kantorovich-Rubinstein duality is the following: if $f:[0,1]^d \rightarrow \infty$ is Lipschitz and $\left\{x_1, \dots, x_N \right\} \subset [0,1]^d$, then $$ \left| \int_{[0,1]^d} f(x) dx - \frac{1}{N}…

Probability · Mathematics 2020-10-27 Stefan Steinerberger

We address the double bubble problem for the anisotropic Grushin perimeter $P_\alpha$, $\alpha\geq 0$, and the Lebesgue measure in $\mathbb R^2$, in the case of two equal volumes. We assume that the contact interface between the bubbles…

Optimization and Control · Mathematics 2023-09-07 Valentina Franceschi , Giorgio Stefani

Uniformity testing and the more general identity testing are well studied problems in distributional property testing. Most previous work focuses on testing under $L_1$-distance. However, when the support is very large or even continuous,…

Machine Learning · Computer Science 2017-10-31 Shichuan Deng , Wenzheng Li , Xuan Wu

Let $\mathbb P$ be any Borel probability measure on the $L^2$-Wasserstein space $(\mathscr{P}_2(M),W_2)$ over a closed Riemannian manifold $M$. We consider the Dirichlet form $\mathcal E$ induced by $\mathbb P$ and by the Wasserstein…

Functional Analysis · Mathematics 2020-02-25 Lorenzo Dello Schiavo

We propose of an improved version of the ubiquitous symmetrization inequality making use of the Wasserstein distance between a measure and its reflection in order to quantify the symmetry of the given measure. An empirical bound on this…

Statistics Theory · Mathematics 2020-01-07 Adam B Kashlak

The Wasserstein distance has emerged as a key metric to quantify distances between probability distributions, with applications in various fields, including machine learning, control theory, decision theory, and biological systems.…

Machine Learning · Computer Science 2026-02-10 Eduardo Figueiredo , Steven Adams , Luca Laurenti

We consider the problem of minimizing the second conformal eigenvalue of the conformal Laplacian in a conformal class of metrics with renormalized volume. We prove, in dimensions $n\in\left\{3,\dotsc,10\right\}$, that a minimizer for this…

Differential Geometry · Mathematics 2024-08-16 Bruno Premoselli , Jérôme Vétois

We estimate the rate of convergence for the Kantorovich (or Wasserstein) distance between empirical measures of i.i.d. random variables associated with the Laguerre model of order $\alpha$ on $(0,\infty)^N$ and their common law, which is…

Probability · Mathematics 2023-08-22 Huaiqian Li , Bingyao Wu

We prove some regularity results for a connected set S in the planar domain O, which minimizes the compliance of its complement O\S, plus its length. This problem, interpreted as to find the best location for attaching a membrane subject to…

Optimization and Control · Mathematics 2016-04-18 Antonin Chambolle , Jimmy Lamboley , Antoine Lemenant , Eugene Stepanov

We consider the nonconvex minimization problem, with quartic objective function, that arises in the exact recovery of a configuration matrix $P\in \R^{nd}$ of $n$ points when a Euclidean distance matrix, \EDMp, is given with embedding…

Optimization and Control · Mathematics 2025-07-29 Mengmeng Song , Douglas Goncalves , Woosuk L. Jung , Carlile Lavor , Antonio Mucherino , Henry Wolkowicz

Among other things, we prove that, for a doubling weight $w$, $0< p\leq\infty$, $r\in{\mathbb N}_0$, and $0<\alpha <r+1 - 1/\lambda_p$, we have \[ E_n(f)_{p, w_n} = O(n^{-\alpha}) \iff \omega_\varphi^{r+1}(f, n^{-1})_{p, w_n} =…

Classical Analysis and ODEs · Mathematics 2015-07-20 Kirill A. Kopotun

Optimal transport theory has recently been extended to quantum settings, where the density matrices generalize the probability measures. In this paper, we study the computational aspects of the order 2 quantum Wasserstein distance,…

Optimization and Control · Mathematics 2025-11-27 Saroj Prasad Chhatoi , Victor Magron

The subject of this paper is the estimation of a probability measure on ${\mathbb R}^d$ from data observed with an additive noise, under the Wasserstein metric of order $p$ (with $p\geq 1$). We assume that the distribution of the errors is…

Statistics Theory · Mathematics 2013-07-22 Jérôme Dedecker , Bertrand Michel

We consider the minimization problem of $\phi$-divergences between a given probability measure $P$ and subsets $\Omega$ of the vector space $\mathcal{M}_\mathcal{F}$ of all signed finite measures which integrate a given class $\mathcal{F}$…

Probability · Mathematics 2010-04-26 Michel Broniatowski , Amor Keziou

We consider the problem of minimizing the Lagrangian $\int [F(\nabla u)+f\,u]$ among functions on $\Omega\subset\mathbb{R}^N$ with given boundary datum $\varphi$. We prove Lipschitz regularity up to the boundary for solutions of this…

Analysis of PDEs · Mathematics 2015-04-24 Pierre Bousquet , Lorenzo Brasco

We consider the 2-dimensional random matching problem in $\mathbb{R}^2.$ In a challenging paper, Caracciolo et. al. arXiv:1402.6993 on the basis of a subtle linearization of the Monge Ampere equation, conjectured that the expected value of…

Mathematical Physics · Physics 2020-08-26 Dario Benedetto , Emanuele Caglioti

We propose a new approach for unsupervised alignment of heterogeneous datasets, which maps data from two different domains without any known correspondences to a common metric space. Our method is based on an unbalanced optimal transport…

Machine Learning · Computer Science 2025-05-14 Florian Beier , Moritz Piening , Robert Beinert , Gabriele Steidl