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Distributionally robust optimization has emerged as an attractive way to train robust machine learning models, capturing data uncertainty and distribution shifts. Recent statistical analyses have proved that generalization guarantees of…

Optimization and Control · Mathematics 2025-01-28 Tam Le , Jérôme Malick

Measuring dependence between random variables is a fundamental problem in Statistics, with applications across diverse fields. While classical measures such as Pearson's correlation have been widely used for over a century, they have…

Statistics Theory · Mathematics 2025-10-08 Marta Catalano , Hugo Lavenant

We consider convex sets whose modulus of convexity is uniformly quadratic. First, we observe several interesting relations between different positions of such ``2-convex'' bodies; in particular, the isotropic position is a finite…

Functional Analysis · Mathematics 2007-05-23 Boaz Klartag , Emanuel Milman

We show that the algebra of cylinder functions in the Wasserstein Sobolev space $H^{1,q}(\mathcal{P}_p(X,\mathsf{d}), W_{p, \mathsf{d}}, \mathfrak{m})$ generated by a finite and positive Borel measure $\mathfrak{m}$ on the…

Functional Analysis · Mathematics 2023-09-06 Giacomo Enrico Sodini

We propose a new class of Markov chain Monte Carlo methods, called $k$-polar slice sampling ($k$-PSS), as a technical tool that interpolates between and extrapolates beyond uniform and polar slice sampling. By examining Wasserstein…

Statistics Theory · Mathematics 2023-11-08 Philip Schär

The squared Wasserstein distance is a natural quantity to compare probability distributions in a non-parametric setting. This quantity is usually estimated with the plug-in estimator, defined via a discrete optimal transport problem which…

Optimization and Control · Mathematics 2020-10-30 Lenaic Chizat , Pierre Roussillon , Flavien Léger , François-Xavier Vialard , Gabriel Peyré

In the density estimation model, we investigate the problem of constructing adaptive honest confidence sets with radius measured in Wasserstein distance $W_p$, $p\geq1$, and for densities with unknown regularity measured on a Besov scale.…

Statistics Theory · Mathematics 2021-11-18 Neil Deo , Thibault Randrianarisoa

Projection robust Wasserstein (PRW) distance, or Wasserstein projection pursuit (WPP), is a robust variant of the Wasserstein distance. Recent work suggests that this quantity is more robust than the standard Wasserstein distance, in…

Machine Learning · Computer Science 2023-01-03 Tianyi Lin , Chenyou Fan , Nhat Ho , Marco Cuturi , Michael I. Jordan

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

This paper extends our earlier results to higher dimensions using a different approach, based on the rigidity of complex structures on certain domains.

Differential Geometry · Mathematics 2011-04-22 X-X. Chen , S. K. Donaldson

We consider the torsional rigidity and the principal eigenvalue related to the $p$-Laplace operator. The goal is to find upper and lower bounds to products of suitable powers of the quantities above in various classes of domains. The limit…

Analysis of PDEs · Mathematics 2021-05-21 Briani Luca , Buttazzo Giuseppe , Prinari Francesca

We set up a general theory for a quantum Wasserstein distance of order 1 in an operator algebraic framework, extending recent work in finite dimensions. In addition, this theory applies not only to states, but also to channels, giving a…

Quantum Physics · Physics 2023-10-05 Rocco Duvenhage , Mathumo Mapaya

We consider a class of piecewise hyperbolic maps from the unit square to itself preserving a contracting foliation and inducing a piecewise expanding quotient map, with infinite derivative (like the first return maps of Lorenz like flows).…

Dynamical Systems · Mathematics 2017-10-05 Stefano Galatolo , Isaia Nisoli

We elucidate why the 1-Wasserstein distance $W_1$ coincides with the area between the two marginal cumulative distribution functions (CDFs). We first describe the Wasserstein distance in terms of copulas, and then show that $W_1$ with the…

Statistics Theory · Mathematics 2021-11-08 Marco De Angelis , Ander Gray

In this paper we investigate properties of metric projections onto specific closed and geodesically convex proper subsets of Wasserstein spaces $(\mathcal{P}_p(\mathbf{R}^d),W_p).$ When $d=1$, as $(\mathcal{P}_2(\mathbf{R}),W_2)$ is…

Functional Analysis · Mathematics 2025-09-03 Anshul Adve , Alpár Mészáros

We prove $L^p$-mass concentration properties of Laplace eigenfunctions away from their nodal sets, extending a recent result in \cite{GM3} to all dimensions, and giving a slight refinement of a result in \cite{JN}. As a consequence, we are…

Analysis of PDEs · Mathematics 2021-10-01 Mayukh Mukherjee

We study the stability of entropically regularized optimal transport with respect to the marginals. Lipschitz continuity of the value and H\"older continuity of the optimal coupling in $p$-Wasserstein distance are obtained under general…

Optimization and Control · Mathematics 2022-07-06 Stephan Eckstein , Marcel Nutz

We provide some non asymptotic bounds, with explicit constants, that measure the rate of convergence, in expected Wasserstein distance, of the empirical measure associated to an i.i.d. $N$-sample of a given probability distribution on…

Probability · Mathematics 2023-03-15 Nicolas Fournier

Motivated by Kloeckner's result on the isometry group of the quadratic Wasserstein space $\mathcal{W}_2\left(\mathbb{R}^n\right)$, we describe the isometry group $\mathrm{Isom}\left(\mathcal{W}_p (E)\right)$ for all parameters $0 < p <…

Metric Geometry · Mathematics 2024-08-19 György Pál Gehér , Tamás Titkos , Dániel Virosztek

We study posterior rates of contraction in Gaussian process regression with unbounded covariate domain. Our argument relies on developing a Gaussian approximation to the posterior of the leading coefficients of a Karhunen--Lo\'{e}ve…

Statistics Theory · Mathematics 2015-10-06 Anirban Bhattacharya , Debdeep Pati
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