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We propose a new method with $\mathcal{L}_2$ distance that maps one $N$-dimensional distribution to another, taking into account available information about correspondences. We solve the high-dimensional problem in 1D space using an…

Computer Vision and Pattern Recognition · Computer Science 2021-02-19 Hana Alghamdi , Rozenn Dahyot

We study the expected $\mathcal{L}_2$-discrepancy of stratified samples generated from special equi-volume partitions of the unit square. The partitions are defined via parallel lines that are all orthogonal to the diagonal of the square.…

Number Theory · Mathematics 2024-01-02 Florian Pausinger

We motivate and describe a method based on fits with polynomials to test the smoothness of differential distributions. As a demonstration, we apply the method to several measurements of inclusive jet double-differential cross section in the…

High Energy Physics - Phenomenology · Physics 2022-12-23 Patrick L. S. Connor , Radek Žlebčík

We study least deviation of logarithmic derivatives of real-valued polynomials with a fixed root from zero on the segment $[-1;1]$ in the uniform norm with the weight $\sqrt{1-x^2}$ and without it. Basing on results of Komarov and Novak and…

Classical Analysis and ODEs · Mathematics 2015-06-10 Petr Chunaev

In this paper, we examine how far a polynomial in $\mathbb{F}_2[x]$ can be from a squarefree polynomial. For any $\epsilon>0$, we prove that for any polynomial $f(x)\in\mathbb{F}_2[x]$ with degree $n$, there exists a squarefree polynomial…

Number Theory · Mathematics 2019-06-20 Michael Filaseta , Richard A. Moy

New lower bounds on the total variation distance between the distribution of a sum of independent Bernoulli random variables and the Poisson random variable (with the same mean) are derived via the Chen-Stein method. The new bounds rely on…

Information Theory · Computer Science 2013-07-17 Igal Sason

In this paper, we consider projection estimates for L\'evy densities in high-frequency setup. We give a unified treatment for different sets of basis functions and focus on the asymptotic properties of the maximal deviation distribution for…

Probability · Mathematics 2016-01-18 Valentin Konakov , Vladimir Panov

A Littlewood polynomial is a single-variable polynomial all of whose coefficients lie in $\{ \pm 1\}$. We establish the leading term asymptotics of the number of reciprocal or skew-reciprocal Littlewood polynomials with square discriminant.…

Number Theory · Mathematics 2025-06-11 David Hokken

The large deviation principle is established for the distributions of a class of generalized stochastic porous media equations for both small noise and short time.

Probability · Mathematics 2007-05-23 Michael Röckner , Feng-Yu Wang , Liming Wu

We formulate Vojta's conjecture for smooth weighted projective varieties, weighted multiplier ideal sheaves, and weighted log pairs and prove that all three versions of the conjecture are equivalent. In the process, we introduce generalized…

Algebraic Geometry · Mathematics 2025-11-19 Sajad Salami , Tony Shaska

In this paper we propose a method to construct probability measures on the space of convex bodies with a given pushforward distribution. Concretely we show that there is a measure on the metric space of centrally symmetric convex bodies,…

Probability · Mathematics 2012-04-27 Á. G. Horváth

We analyze monotone difference schemes for strongly degenerate convection-diffusion equations in one spatial dimension. These nonlinear equations are well-posed within a class of (discontinuous) entropy solutions. We prove that the L1…

Analysis of PDEs · Mathematics 2013-04-16 Kenneth H. Karlsen , Nils Henrik Risebro , Erlend B. Storrøsten

Log-Euclidean distances are commonly used to quantify the similarity between positive definite matrices using geometric considerations. This paper analyzes the behavior of this distance when it is used to measure closeness between…

Signal Processing · Electrical Eng. & Systems 2024-08-09 Xavier Mestre , Roberto Pereira

The free distance of a convolutional code is a reliable indicator of its performance. However its computation is not an easy task. In this paper, we present some algorithms to compute the free distance with good efficiency that work for…

Information Theory · Computer Science 2024-02-06 Zita Abreu , Joachim Rosenthal , Michael Schaller

The paper investigates the problem of performing correlation analysis when the number of observations is very large. In such a case, it is often necessary to combine the random observations to achieve dimensionality reduction of the…

Information Theory · Computer Science 2020-10-19 Pavel Loskot

We consider the convex hull of a finite sample of i.i.d. points uniformly distributed in a convex body in $\R^d$, $d\geq 2$. We prove an exponential deviation inequality, which leads to rate optimal upper bounds on all the moments of the…

Statistics Theory · Mathematics 2013-11-13 Victor-Emmanuel Brunel

We derive exponential bounds on probabilities of large deviations for "light tail" martingales taking values in finite-dimensional normed spaces. Our primary emphasis is on the case where the bounds are dimension-independent or nearly so.…

Probability · Mathematics 2023-01-31 Anatoli Juditsky , Arkadii S. Nemirovski

We give an estimate for the Kolmogorov distance between an infinitely divisible distribution (with mean zero and variance one) and the standard Gaussian distribution in terms of the difference between the fourth moment and 3. In a similar…

Probability · Mathematics 2014-02-26 Octavio Arizmendi , Arturo Jaramillo

The capacity to devise order metrics for microstructures of multiphase heterogeneous media is a highly challenging task, given the richness of the possible geometries and topologies of the phases that can arise. This investigation initiates…

Soft Condensed Matter · Physics 2022-07-20 Salvatore Torquato , Murray Skolnick , Jaeuk Kim

This report presents a new, algorithmic approach to the distributions of the distance between two points distributed uniformly at random in various polygons, based on the extended Kinematic Measure (KM) from integral geometry. We first…

Computational Geometry · Computer Science 2016-02-11 Fei Tong , Jianping Pan