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In the paper we prove two inequalities in the setting of ${\sf RCD}(K,\infty)$ spaces using similar techniques. The first one is an indeterminacy estimate involving the $p$-Wasserstein distance between the positive part and the negative…

Differential Geometry · Mathematics 2022-02-08 Nicolò De Ponti , Sara Farinelli

Impractical assumptions, an inherently myopic nature, and the crucial role of the initial design, all together contribute to making theoretical convergence proofs of little value in real-life Bayesian Optimization applications. In this…

Optimization and Control · Mathematics 2026-02-13 Antonio Candelieri , Francesco Archetti

We show that capacity can be computed with locally Lipschitz functions in locally complete and separable metric spaces. Further, we show that if $(X,d,\mu)$ is a locally complete and separable metric measure space, then continuous functions…

Metric Geometry · Mathematics 2023-11-14 Sylvester Eriksson-Bique , Pietro Poggi-Corradini

The quantization problem aims to find the best possible approximation of probability measures on ${\mathbb{R}}^d$ using finite, discrete measures. The Wasserstein distance is a typical choice to measure the quality of the approximation.…

Probability · Mathematics 2023-09-11 Rajmadan Lakshmanan , Alois Pichler

Conditional expectation \mathbb{E}(Y \mid X) often fails to capture the complexity of multimodal conditional distributions \mathcal{L}(Y \mid X). To address this, we propose using n-point conditional quantizations--functional mappings of X…

Machine Learning · Computer Science 2025-05-21 Blaise Delattre , Sylvain Delattre , Alexandre Vérine , Alexandre Allauzen

H-measures and semiclassical (Wigner) measures were introduced in earlyn 1990s and since then they have found numerous applications in problems involving $\mathrm{L}^2$ weakly converging sequences. Although they are similar objects, neither…

Analysis of PDEs · Mathematics 2023-09-06 Nenad Antonić , Marko Erceg

This paper considers the problem of $L^p$-estimates for a certain multilinear functional involving integration against a kernel with the structure of a determinant. Examples of such objects are ubiquitous in the study of Fourier restriction…

Classical Analysis and ODEs · Mathematics 2009-11-09 Philip T. Gressman

Seismic signals are typically compared using travel time difference or $L_2$ difference. We propose the Wasserstein metric as an alternative measure of fidelity or misfit in seismology. It exhibits properties from both of the traditional…

Mathematical Physics · Physics 2013-11-20 Bjorn Engquist , Brittany D. Froese

Given a compactly supported probability measure on a Riemannian manifold, we study the asymptotic speed at which it can be approximated (in Wasserstein distance of any exponent p) by finitely supported measure. This question has been…

Optimization and Control · Mathematics 2012-07-17 Benoit Kloeckner

This paper presents a novel multi-scale method for elliptic partial differential equations with arbitrarily rough coefficients. In the spirit of numerical homogenization, the method constructs problem-adapted ansatz spaces with uniform…

Numerical Analysis · Mathematics 2024-08-05 Philip Freese , Moritz Hauck , Tim Keil , Daniel Peterseim

Assume that we observe i.i.d.~points lying close to some unknown $d$-dimensional $\mathcal{C}^k$ submanifold $M$ in a possibly high-dimensional space. We study the problem of reconstructing the probability distribution generating the…

Statistics Theory · Mathematics 2022-02-15 Vincent Divol

We study $L_q$-approximation and integration for functions from the Sobolev space $W^s_p(\Omega)$ and compare optimal randomized (Monte Carlo) algorithms with algorithms that can only use iid sample points, uniformly distributed on the…

Numerical Analysis · Mathematics 2021-08-05 David Krieg , Erich Novak , Mathias Sonnleitner

We construct geodesics in the Wasserstein space of probability measure along which all the measures have an upper bound on their density that is determined by the densities of the endpoints of the geodesic. Using these geodesics we show…

Differential Geometry · Mathematics 2011-11-24 Tapio Rajala

Suppose that we wish to estimate a vector $\mathbf{x}$ from a set of binary paired comparisons of the form "$\mathbf{x}$ is closer to $\mathbf{p}$ than to $\mathbf{q}$" for various choices of vectors $\mathbf{p}$ and $\mathbf{q}$. The…

Machine Learning · Statistics 2021-08-31 Andrew K. Massimino , Mark A. Davenport

Borel probability measures living on metric spaces are fundamental mathematical objects. There are several meaningful distance functions that make the collection of the probability measures living on a certain space a metric space. We are…

Functional Analysis · Mathematics 2018-06-14 Dániel Virosztek

From the observation of a diffusion path $(X_t)_{t\in [0,T]}$ on a compact connected $d$-dimensional manifold $\mathcal{M}$ without boundary, we consider the problem of estimating the stationary measure $\mu$ of the process. Wang and Zhu…

Statistics Theory · Mathematics 2026-01-12 Vincent Divol , Hélène Guérin , Dinh-Toan Nguyen , Viet Chi Tran

We give concentration inequalities in Wasserstein distance for the empirical measure of a sequence of independent and identically distributed random variables with values in a Polish space E. These inequalities involve the covering…

Probability · Mathematics 2026-01-19 Jérôme Dedecker , Aurélie Fischer , Bertrand Michel

We introduce the concept of functions of locally bounded variation on abstract Wiener spaces and study their properties. Some nontrivial examples and applications to stochastic analysis are also discussed.

Probability · Mathematics 2019-09-16 Masanori Hino

We establish new quantitative estimates for localized finite differences of solutions to the Poisson problem for the fractional Laplace operator with homogeneous Dirichlet conditions of solid type settled in bounded domains satisfying the…

Analysis of PDEs · Mathematics 2016-06-22 Goro Akagi , Giulio Schimperna , Antonio Segatti , Laura V. Spinolo

Let q^n be a continuous density function in n-dimensional Euclidean space. We think of q^n as the density function of some random sequence X^n with values in \BbbR^n. For I\subset[1,n], let X_I denote the collection of coordinates X_i, i\in…

Probability · Mathematics 2016-09-07 Katalin Marton