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In the present paper we obtain fully explicit large deviation inequalities for empirical processes indexed by a Vapnik--Chervonenkis class of sets (or functions). Furthermore we illustrate the importance of such results for the theory of…

Probability · Mathematics 2015-04-02 Christoph Aistleitner

We extend results of Damanik and Tcheremchantsev on estimating transport exponents to initial states supported on more than one site. These general results for upper and lower bounds are then applied to several classes of models, including…

Spectral Theory · Mathematics 2016-10-19 Vitalii Gerbuz

We develop a mathematical theory of entropic regularisation of unbalanced optimal transport problems. Focusing on static formulation and relying on the formalism developed for the unregularised case, we show that unbalanced optimal…

Optimization and Control · Mathematics 2023-05-05 Maciej Buze , Manh Hong Duong

The matrix version of the entropy-power inequality for real or complex coefficients and variables is proved using a transportation argument that easily settles the equality case. An application to blind source extraction is given.

Information Theory · Computer Science 2019-06-04 Olivier Rioul , Ram Zamir

This paper is concerned with a posteriori error bounds for linear transport equations and related questions of contriving corresponding adaptive solution strategies in the context of Discontinuous-Petrov-Galerkin schemes. After indicating…

Numerical Analysis · Mathematics 2019-02-22 W. Dahmen , R. P. Stevenson

We focus on Optimal Transport PDE on the unit sphere $\mathbb{S}^2$ with a particular type of cost function $c(x,y) = F(x \cdot y, x \cdot \hat{e}, y \cdot \hat{e})$ which we call cost functions with preferential direction, where $\hat{e}…

Analysis of PDEs · Mathematics 2024-07-11 Axel G. R. Turnquist

In recent years, Bayesian inference in large-scale inverse problems found in science, engineering and machine learning has gained significant attention. This paper examines the robustness of the Bayesian approach by analyzing the stability…

Machine Learning · Statistics 2023-03-06 Alfredo Garbuno-Inigo , Tapio Helin , Franca Hoffmann , Bamdad Hosseini

This chapter reviews indirect estimators of intergenerational mobility, focusing on approaches that infer parent-child or other family associations when direct income data are incomplete or unavailable. We synthesize methods based on…

General Economics · Economics 2026-05-20 Andrea Del Pizzo , Martin Nybom , Jan Stuhler

This paper deals with the problem of quantifying the impact of model misspecification when computing general expected values of interest. The methodology that we propose is applicable in great generality, in particular, we provide examples…

Probability · Mathematics 2017-07-04 Jose Blanchet , Karthyek R. A. Murthy

This work focuses on exact methods for a Simultaneous Vehicle Routing and Crew Scheduling Problem in long-haul transport. Pickup-and-delivery requests with time windows must be fullfiled over a multi-day planning horizon. Unlike some…

Optimization and Control · Mathematics 2024-05-31 Mauro Lucci , Daniel Severin , Paula Zabala

We investigate the convergence rate of the optimal entropic cost $v_\varepsilon$ to the optimal transport cost as the noise parameter $\varepsilon \downarrow 0$. We show that for a large class of cost functions $c$ on $\mathbb{R}^d\times…

Optimization and Control · Mathematics 2022-06-08 Guillaume Carlier , Paul Pegon , Luca Tamanini

In this pedagogical text aimed at those wanting to start thinking about or brush up on probabilistic inference, I review the rules by which probability distribution functions can (and cannot) be combined. I connect these rules to the…

Data Analysis, Statistics and Probability · Physics 2012-05-22 David W. Hogg

Distribution functions of many static transport equations are found using the Maximum Entropy Principle. The equations of constraint which contain the relevant dynamical information are simply the low-lying moments of the distributions.…

Statistical Mechanics · Physics 2020-04-22 J. A. Secrest , J. M. Conroy , H. G. Miller

For probability measures on countable spaces we derive distributional limits for empirical entropic optimal transport quantities. More precisely, we show that the empirical optimal transport plan weakly converges to a centered Gaussian…

Probability · Mathematics 2022-12-27 Shayan Hundrieser , Marcel Klatt , Axel Munk

We introduce and investigate properties of a variant of the semi-discrete optimal transport problem. In this problem, one is given an absolutely continuous source measure and cost function, along with a finite set which will be the support…

Analysis of PDEs · Mathematics 2019-09-13 Mohit Bansil , Jun Kitagawa

It is well-known that the optimal transport problem on the real line for the classical distance cost may not have a unique solution. In this paper we recover uniqueness by considering the transport problems where the costs are a power…

Probability · Mathematics 2019-07-02 Nicolas Juillet

In this article we consider a method of proving a class of inequalities of the form (1). The method is based on the precise approximations of the sine and cosine functions by Maclaurin polynomials of given order. By using this method we…

Classical Analysis and ODEs · Mathematics 2019-10-15 Branko Malesevic , Milica Makragic

The unavoidable travel time variability in transportation networks, resulted from the widespread supply side and demand side uncertainties, makes travel time reliability (TTR) be a common and core interest of all the stakeholders in…

General Economics · Economics 2022-12-13 Zhaoqi Zang , Xiangdong Xu , Kai Qu , Ruiya Chen , Anthony Chen

Many causal and structural parameters in economics can be identified and estimated by computing the value of an optimization program over all distributions consistent with the model and the data. Existing tools apply when the data is…

Econometrics · Economics 2025-07-31 Andrei Voronin

This paper introduces a comprehensive framework for complex-valued probability measures and explores their novel applications in information theory and statistical analysis. We define a complex probability measure as a phase-modulated…

Information Theory · Computer Science 2026-03-16 Siang Cheng , Hejun Xu , Tianxiao Pang
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