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This article presents a theoretical study of uncertainty functionals on general measurable spaces. These functionals are fundamental in experimental design and global sensitivity analysis, where they are used to quantify variability and…

Statistics Theory · Mathematics 2026-05-19 Julien Bect , Xujia Zhu

We show that domains, that allow for convex functions with unbounded gradient at their boundary, are convex.

Classical Analysis and ODEs · Mathematics 2007-05-23 Oliver C. Schnürer

The paper reexamines an argument by Talagrand that leads to a remarkable exponential tail bound for the concentration of probability near a set. The main novelty is the replacement of a mysterious Calculus inequality by an application of…

Probability · Mathematics 2007-05-23 David Pollard

Let $K\subseteq{\mathbb R}^n$ be a convex semialgebraic set. The semidefinite extension degree ${\mathrm{sxdeg}}(K)$ of $K$ is the smallest number $d$ such that $K$ is a linear image of an intersection of finitely many spectrahedra, each of…

Algebraic Geometry · Mathematics 2024-10-15 Claus Scheiderer

We construct a family of countexamples to a conjecture of Galvin [5], which stated that for any $n$-vertex, $d$-regular graph $G$ and any graph $H$ (possibly with loops), \[\hom(G,H) \leq \max\left\lbrace\hom(K_{d,d}, H)^{\frac{n}{2d}},…

Combinatorics · Mathematics 2017-03-09 Luke Sernau

Let $(M,d)$ be a separable and complete geodesic space with curvature lower bounded, by $\kappa\in \mathbb R$, in the sense of Alexandrov. Let $\mu$ be a Borel probability measure on $M$, such that $\mu\in\mathcal P_2(M)$, and that has at…

Metric Geometry · Mathematics 2021-03-30 Quentin Paris

Geometrically convex functions constitute an interesting class of functions obtained by replacing the arithmetic mean with the geometric mean in the definition of convexity. As recently suggested, geometric convexity may be a sensible…

Risk Management · Quantitative Finance 2024-03-12 Mücahit Aygün , Fabio Bellini , Roger J. A. Laeven

A "law of large numbers" for consecutive convex hulls for weakly dependent Gaussian sequences $\{X_n\}$, having the same marginal distribution, is extended to the case when the sequence $\{X_n\}$ has a weak limit. Let $\mathbb{B}$ be a…

Probability · Mathematics 2020-05-13 Youri Davydov , Vygantas Paulauskas

This study focuses on convex functions and their generalized. Thus, we start this study by giving the definition of convex functions and some of their properties and discussing a simple geometric property. Then we generalize E-convex…

Classical Analysis and ODEs · Mathematics 2017-04-27 Adem Kilicman , Wedad Saleh

This note demonstrates that it is possible to bound the expectation of an arbitrary norm of a random matrix drawn from the Stiefel manifold in terms of the expected norm of a standard Gaussian matrix with the same dimensions. A related…

Probability · Mathematics 2014-04-29 Joel A. Tropp

We study the convolution function $$ C[f(x)] := \int_1^x f(y)f({x\over y}) {{\rm d} y\over y} $$ when $f(x)$ is a suitable number-theoretic error term. Asymptotics and upper bounds for $C[f(x)]$ are derived from mean square bounds for…

Number Theory · Mathematics 2010-11-03 Aleksandar Ivic

We study the local and global versions of the convexity, which is closely related to the problem of extending a convex function on a non-convex domain to a convex function on the convex hull of the domain and beyond the convex hull. We also…

Classical Analysis and ODEs · Mathematics 2013-08-08 Min Yan

Generalization error bounds are essential to understanding machine learning algorithms. This paper presents novel expected generalization error upper bounds based on the average joint distribution between the output hypothesis and each…

Information Theory · Computer Science 2022-02-25 Gholamali Aminian , Yuheng Bu , Gregory Wornell , Miguel Rodrigues

In this paper functions $f:D\to\mathbb{R}$ satisfying the inequality \[ f\Big(\frac{x+y}{2}\Big)\leq\frac12f(x)+\frac12f(y) +\varphi\Big(\frac{x-y}{2}\Big) \qquad(x,y\in D) \] are studied, where $D$ is a nonempty convex subset of a real…

Classical Analysis and ODEs · Mathematics 2024-12-10 Gábor Marcell Molnár , Zsolt Páles

This paper proposes a new sharpened version of the Jensen's inequality. The proposed new bound is simple and insightful, is broadly applicable by imposing minimum assumptions, and provides fairly accurate result in spite of its simple form.…

Statistics Theory · Mathematics 2017-10-26 J. G. Liao , Arthur Berg

We examine the metrics that arise when a finite set of points is embedded in the real line, in such a way that the distance between each pair of points is at least 1. These metrics are closely related to some other known metrics in the…

Combinatorics · Mathematics 2011-08-02 Adam N. Letchford , Hanna Seitz , Dirk Oliver Theis

Convex functions have played a major role in the field of Mathematical inequalities. In this paper, we introduce a new concept related to convexity, which proves better estimates when the function is somehow more convex than another. In…

Functional Analysis · Mathematics 2020-03-25 M. Sababheh , S. Furuichi , H. R. Moradi

In the present investigation, by applying two different normalizations of the Jackson and Hahn-Exton $q$-Bessel functions tight lower and upper bounds for the radii of convexity of the same functions are obtained. In addition, it was shown…

Complex Variables · Mathematics 2017-02-16 Halit Orhan , İbrahim Aktaş

Let $G$ be a graph and let $g, f$ be nonnegative integer-valued functions defined on $V(G)$ such that $g(v) \le f(v)$ and $g(v) \equiv f(v) \pmod{2}$ for all $v \in V(G)$. A $(g,f)$-parity factor of $G$ is a spanning subgraph $H$ such that…

Combinatorics · Mathematics 2021-11-29 Donggyu Kim , Suil O

Metric graph properties lie in the heart of the analysis of complex networks, while in this paper we study their convexity through mathematical definition of a convex subgraph. A subgraph is convex if every geodesic path between the nodes…

Social and Information Networks · Computer Science 2018-05-31 Tilen Marc , Lovro Šubelj