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We investigate the minimum cost of a wide class of combinatorial optimization problems over random bipartite geometric graphs in $\mathbb{R}^d$ where the edge cost between two points is given by a $p$-th power of their Euclidean distance.…

Probability · Mathematics 2023-07-20 Michael Goldman , Dario Trevisan

We prove a Central Limit Theorem for the empirical optimal transport cost, $\sqrt{\frac{nm}{n+m}}\{\mathcal{T}_c(P_n,Q_m)-\mathcal{T}_c(P,Q)\}$, in the semi discrete case, i.e when the distribution $P$ is supported in $N$ points, but…

Probability · Mathematics 2022-02-15 Eustasio del Barrio , Alberto González-Sanz , Jean-Michel Loubes

Following (Shevtsova, 2010) we introduce detailed classification of the asymptotically exact constants in natural estimates of the rate of convergence in the Lindeberg central limit theorem, namely in Esseen's, Rozovskii's, and Wang-Ahmad's…

Probability · Mathematics 2021-01-13 Ruslan Gabdullin , Vladimir Makarenko , Irina Shevtsova

For a finite metric graph $X=(V,E,\ell)$, where $V$ is endowed with the shortest path metric, we consider the transportation cost problem associated with the distance $d$ on $V$. Namely, for $f$ a function with total sum 0 on $V$, write…

Metric Geometry · Mathematics 2026-01-26 Georges Skandalis , Alain Valette

In this work, we study convergence in probability and almost sure convergence for weighted partial sums of random variables that are related to the class of generalized Oppenheim expansions. It is worth noting that the random variables…

Probability · Mathematics 2022-07-21 Rita Giuliano , Milto Hadjikyriakou

We study the asymptotic properties of geodesically convex $M$-estimation on non-linear spaces. Namely, we prove that under very minimal assumptions besides geodesic convexity of the cost function, one can obtain consistency and asymptotic…

Statistics Theory · Mathematics 2023-05-08 Victor-Emmanuel Brunel

This paper considers nonconvex distributed constrained optimization over networks, modeled as directed (possibly time-varying) graphs. We introduce the first algorithmic framework for the minimization of the sum of a smooth nonconvex…

Optimization and Control · Mathematics 2018-09-05 Gesualdo Scutari , Ying Sun

We develop an $\e$-regularity theory at the boundary for a general class of Monge-Amp\`ere type equations arising in optimal transportation. As a corollary we deduce that optimal transport maps between H\"older densities supported on $C^2$…

Analysis of PDEs · Mathematics 2014-12-19 Shibing Chen , Alessio Figalli

The central limit theorem for convex bodies says that with high probability the marginal of an isotropic log-concave distribution along a random direction is close to a Gaussian, with the quantitative difference determined asymptotically by…

Functional Analysis · Mathematics 2019-10-01 Haotian Jiang , Yin Tat Lee , Santosh S. Vempala

In this paper we study approximations for boundary crossing probabilities for the moving sums of i.i.d. normal random variables. We propose approximating a discrete time problem with a continuous time problem allowing us to apply developed…

Statistics Theory · Mathematics 2019-04-30 Jack Noonan , Anatoly Zhigljavsky

This paper is devoted to the study of couplings of the Lebesgue measure and the Poisson point process. We prove existence and uniqueness of an optimal coupling whenever the asymptotic mean transportation cost is finite. Moreover, we give…

Probability · Mathematics 2013-08-14 Martin Huesmann , Karl-Theodor Sturm

While there is extensive literature on approximation, deterministic as well as random, of general convex bodies $K$ in the symmetric difference metric, or other metrics arising from intrinsic volumes, very little is known for corresponding…

Metric Geometry · Mathematics 2025-08-25 Joscha Prochno , Carsten Schütt , Mathias Sonnleitner , Elisabeth M. Werner

We investigate in this work a versatile convex framework for multiple image segmentation, relying on the regularized optimal mass transport theory. In this setting, several transport cost functions are considered and used to match…

Computer Vision and Pattern Recognition · Computer Science 2016-10-06 Nicolas Papadakis , Julien Rabin

We develop an inferential toolkit for analyzing object-valued responses, which correspond to data situated in general metric spaces, paired with Euclidean predictors within the conformal framework. To this end we introduce conditional…

Methodology · Statistics 2025-07-01 Hang Zhou , Hans-Georg Müller

We address the problem of distributed uncon- strained convex optimization under separability assumptions, i.e., the framework where each agent of a network is endowed with a local private multidimensional convex cost, is subject to…

Optimization and Control · Mathematics 2015-11-06 Damiano Varagnolo , Filippo Zanella , Angelo Cenedese , Gianluigi Pillonetto , Luca Schenato

We prove that if a rectangular matrix with uniformly small entries and approximately orthogonal rows is applied to the independent standardized random variables with uniformly bounded third moments, then the empirical CDF of the resulting…

Probability · Mathematics 2007-06-14 Bernard Bercu , Wlodzimierz Bryc

The work of this paper is devoted to obtaining strong laws for intermediately trimmed sums of random variables with infinite means. Particularly, we provide conditions under which the intermediately trimmed sums of independent but not…

Probability · Mathematics 2023-10-03 Rita Giuliano , Milto Hadjikyriakou

In compact settings, the convergence rate of the empirical optimal transport cost to its population value is well understood for a wide class of spaces and cost functions. In unbounded settings, however, hitherto available results require…

Statistics Theory · Mathematics 2024-07-24 Thomas Staudt , Shayan Hundrieser

The Koml\'os$\unicode{x2013}$Major$\unicode{x2013}$Tusn\'ady (KMT) inequality for partial sums is one of the most celebrated results in probability theory. Yet its practical application has been hindered by a lack of practical constants.…

Statistics Theory · Mathematics 2026-05-19 Haoyu Ye , Morgane Austern

In this paper, we develop a new strategy aimed at obtaining high-order asymptotic models for transport equations with highly-oscillatory solutions. The technique relies upon recent developments averaging theory for ordinary differential…

Numerical Analysis · Mathematics 2016-11-15 Philippe Chartier , Nicolas Crouseilles , Mohammed Lemou
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