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Related papers: The Hal\'asz-Sz\'ekely Barycenter

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Barycenters (aka Fr\'echet means) were introduced in statistics in the 1940's and popularized in the fields of shape statistics and, later, in optimal transport and matrix analysis. They provide the most natural extension of linear…

Statistics Theory · Mathematics 2023-03-03 Victor-Emmanuel Brunel , Jordan Serres

In this paper, based on the Fr{\'e}chet mean, we define a notion of barycenter corresponding to a usual notion of statistical mean. We prove the existence of Wasserstein barycenters of random distributions defined on a geodesic space (E,…

Statistics Theory · Mathematics 2016-02-15 Thibaut Le Gouic , Jean-Michel Loubes

We study the existence and uniqueness of the barycenter of a signed distribution of probability measures on a Hilbert space. The barycenter is found, as usual, as a minimum of a functional. In the case where the positive part of the signed…

Probability · Mathematics 2025-07-08 Francesco Tornabene , Marco Veneroni , Giuseppe Savaré

We study the barycenter of the Hellinger--Kantorovich metric over non-negative measures on compact, convex subsets of $\mathbb{R}^d$. The article establishes existence, uniqueness (under suitable assumptions) and equivalence between a…

Optimization and Control · Mathematics 2021-01-26 Gero Friesecke , Daniel Matthes , Bernhard Schmitzer

Barycentric averaging is a principled way of summarizing populations of measures. Existing algorithms for estimating barycenters typically parametrize them as weighted sums of Diracs and optimize their weights and/or locations. However,…

Machine Learning · Statistics 2021-02-16 Samuel Cohen , Michael Arbel , Marc Peter Deisenroth

We investigate barycenters of probability measures on Gromov hyperbolic spaces, toward development of convex optimization in this class of metric spaces. We establish a contraction property (the Wasserstein distance between probability…

Metric Geometry · Mathematics 2024-06-18 Shin-ichi Ohta

The Frechet mean or barycenter generalizes the idea of averaging in spaces where pairwise addition is not well-defined. In general metric spaces, the Frechet sample mean is not a consistent estimator of the theoretical Frechet mean. For…

Statistics Theory · Mathematics 2013-05-16 Cedric E. Ginestet

Let $\mathcal{P}_{2,ac}$ be the set of Borel probabilities on $\mathbb{R}^d$ with finite second moment and absolutely continuous with respect to Lebesgue measure. We consider the problem of finding the barycenter (or Fr\'echet mean) of a…

Computation · Statistics 2016-04-25 Pedro C. Álvarez-Esteban , E. del Barrio , J. A. Cuesta-Albertos , C. Matrán

We prove the following isoperimetric type inequality: Given a finite absolutely continuous Borel measure on ${\mathbb R}^n$, halfspaces have maximal measure among all subsets with prescribed barycenter. As a consequence, we make progress…

Probability · Mathematics 2025-07-11 Shoni Gilboa , Pazit Haim-Kislev , Boaz Slomka

We introduce a weak notion of barycenter of a probability measure $\mu$ on a metric measure space $(X, d, {\bf m})$, with the metric $d$ and reference measure ${\bf m}$. Under the assumption that optimal transport plans are given by…

Optimization and Control · Mathematics 2017-03-30 Young-Heon Kim , Brendan Pass

Wasserstein barycenters define averages of probability measures in a geometrically meaningful way. Their use is increasingly popular in applied fields, such as image, geometry or language processing. In these fields however, the probability…

Numerical Analysis · Mathematics 2023-03-13 Guillaume Carlier , Alex Delalande , Quentin Merigot

We introduce weak barycenters of a family of probability distributions, based on the recently developed notion of optimal weak transport of mass by Gozlanet al. (2017) and Backhoff-Veraguas et al. (2020). We provide a theoretical analysis…

Machine Learning · Statistics 2023-03-13 Elsa Cazelles , Felipe Tobar , Joaquín Fontbona

We study barycenters in the space of probability measures on a Riemannian manifold, equipped with the Wasserstein metric. Under reasonable assumptions, we establish absolute continuity of the barycenter of general measures $\Omega \in…

Analysis of PDEs · Mathematics 2015-10-05 Young-Heon Kim , Brendan Pass

Barycentric algebras are an abstraction of the notion of convex sets, defined by a set of equations. We study semitopological and topological barycentric algebras, in the spirit of a previous study by Klaus Keimel on semitopological and…

Functional Analysis · Mathematics 2026-05-22 Jean Goubault-Larrecq

We establish a strong law of large numbers and a central limit theorem in the Bures-Wasserstein space of covariance operators -- or equivalently centred Gaussian measures -- over a general separable Hilbert space. Specifically, we show that…

Probability · Mathematics 2024-11-05 Leonardo V. Santoro , Victor M. Panaretos

In this paper, a regularization of Wasserstein barycenters for random measures supported on $\mathbb{R}^{d}$ is introduced via convex penalization. The existence and uniqueness of such barycenters is first proved for a large class of…

Statistics Theory · Mathematics 2019-03-20 Jérémie Bigot , Elsa Cazelles , Nicolas Papadakis

This paper provides rates of convergence for empirical (generalised) barycenters on compact geodesic metric spaces under general conditions using empirical processes techniques. Our main assumption is termed a variance inequality and…

Statistics Theory · Mathematics 2019-06-03 Adil Ahidar-Coutrix , Thibaut Le Gouic , Quentin Paris

We introduce the notions of \textit{conformal barycenter} and \textit{holomorphic barycenter} of a measurable set $D$ in the hyperbolic ball. The two barycenters coincide in the disk, but they differ in multidimensional balls $\mathbb{C}^m…

Differential Geometry · Mathematics 2024-11-26 Vladimir Jacimovic , David Kalaj

We study the problem of model aggregation within the Wasserstein space for probability measures on the real line. Given a fixed finite collection of candidate probability models, we consider the associated class of Wasserstein barycenters…

This paper is concerned with the problem of defining and estimating statistics for distributions on spaces such as Riemannian manifolds and more general metric spaces. The challenge comes, in part, from the fact that statistics such as…

Statistics Theory · Mathematics 2025-05-29 Washington Mio , Tom Needham
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