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Let $U\subseteq\mathbb{R}^d$ be open and convex. We prove that every (not necessarily Lipschitz or strongly) convex function $f:U\to\mathbb{R}$ can be approximated by real analytic convex functions, uniformly on all of $U$. We also show…

Differential Geometry · Mathematics 2014-10-24 Daniel Azagra

A permanental vector is a generalization of a vector with components that are squares of the components of a Gaussian vector, in the sense that the matrix that appears in the Laplace transform of the vector of Gaussian squares is not…

Probability · Mathematics 2011-07-07 Hana Kogan , Michael B. Marcus

A transient stochastic process is considered strongly transient if conditioned on returning to the starting location, the expected time it takes to return the the starting location is finite. We characterize strong transience for a…

Probability · Mathematics 2016-06-14 Jonathon Peterson

We investigate a generalisation of the coherent choice functions considered by Seidenfeld et al. (2010), by sticking to the convexity axiom but imposing no Archimedeanity condition. We define our choice functions on vector spaces of…

Artificial Intelligence · Computer Science 2017-07-12 Arthur Van Camp , Gert de Cooman , Enrique Miranda

Sufficient conditions are given for a function $F(p)$ to be the Laplace transform of a function $f(t)$ or a distribution $f$. No assumption on $f$ is given a priori. It is not even assumed that $f=0$ for $t<0$.

Complex Variables · Mathematics 2024-11-21 Alexander G. Ramm

In this paper we associate with an infinite family of real extended functions defined on a locally convex space, a sum, called robust sum, which is always well-defined. We also associate with that family of functions a dual pair of problems…

Optimization and Control · Mathematics 2018-11-07 Nguyen Dinh , Miguel A. Goberna , Michel Volle

We prove that there exists an absolute constant $\alpha >1$ with the following property: if $K$ is a convex body in ${\mathbb R}^n$ whose center of mass is at the origin, then a random subset $X\subset K$ of cardinality ${\rm…

Metric Geometry · Mathematics 2015-12-16 Silouanos Brazitikos , Giorgos Chasapis , Labrini Hioni

We give an example of a convex, finite and lower semicontinuous function whose subdifferential is everywhere empty. This is possible since the function is defined on an incomplete normed space. The function serves as a universal…

Optimization and Control · Mathematics 2024-09-30 Gerd Wachsmuth

The main goal of this paper is to obtain sufficient conditions so that Le Roy type functions and multivariate Le Roy type functions satisfy subordination of exponential function. Moreover conditions on parameters have been derived to claim…

Complex Variables · Mathematics 2025-03-18 Suhas B Mahesh , Karthik V Pai , Abhinav Sharma

A random vector ${\bf X}$ is weakly stable iff for all $a,b\in \mathbb{R}$ there exists a random variable $\Theta$ such that $a{\bf X}+b{\bf X}'\stackrel{d}{=}{\bf X}\Theta$. This is equivalent (see \cite{MOU}) with the condition that for…

Probability · Mathematics 2007-05-23 Jolanta K. Misiewicz

A method of proving local continuity of concave functions on convex set possessing the $\mu$-compactness property is presented. This method is based on a special approximation of these functions. The class of $\mu$-compact sets can be…

Functional Analysis · Mathematics 2010-06-22 M. E. Shirokov

Consider $n$ iid real-valued random vectors of size $k$ having iid coordinates with a general distribution function $F$. A vector is a maximum if and only if there is no other vector in the sample which weakly dominates it in all…

Probability · Mathematics 2023-02-20 Royi Jacobovic , Or Zuk

In this paper, we investigate and find a necessary and sufficient condition for a function to be absolutely continuous over $\mathbb{R}$ (denoted by $AC(\mathbb{R})$) or any unbounded interval in $\mathbb{R}$ . Note that the Lebesgue's…

Functional Analysis · Mathematics 2025-11-11 Gourav Banerjee

We define in the space of n by m matrices of rank n, n less or equal than m, the condition Riemannian structure as follows: For a given matrix A the tangent space of A is equipped with the Hermitian inner product obtained by multiplying the…

Numerical Analysis · Mathematics 2010-07-12 Carlos Beltrán , Jean-Pierre Dedieu , Gregorio Malajovich , Mike Shub

Motivated by applications to prediction and forecasting, we suggest methods for approximating the conditional distribution function of a random variable Y given a dependent random d-vector X. The idea is to estimate not the distribution of…

Statistics Theory · Mathematics 2007-06-13 Peter Hall , Qiwei Yao

We show that the Rademacher complexity of any $\mathbb{R}^{K}$-valued function class composed with an $\ell_{\infty}$-Lipschitz function is bounded by the maximum Rademacher complexity of the restriction of the function class along each…

Machine Learning · Computer Science 2019-11-18 Dylan J. Foster , Alexander Rakhlin

Let $G\curvearrowright M$ be an isometric action of a Lie Group on a complete orientable Riemannian manifold. We disintegrate absolutely continuous measures with respect to the volume measure of $M$ along the principal orbits of…

Differential Geometry · Mathematics 2023-10-25 André Magalhães de Sá Gomes , Christian S. Rodrigues

A (unit norm) frame is scalable if its vectors can be rescaled so as to result into a tight frame. Tight frames can be considered optimally conditioned because the condition number of their frame operators is unity. In this paper we…

Numerical Analysis · Mathematics 2015-01-27 Chae A. Clark , Kasso A. Okoudjou

Results on the upper and lower semicontinuity of functionals defined on spaces of convex and more general functions are established. In particular, the following result is obtained. Let $\phi(v; \cdot)$ be the density of the absolutely…

Functional Analysis · Mathematics 2025-12-10 Fernanda M. Baêta , Monika Ludwig

Existing analysis of AdaGrad and other adaptive methods for smooth convex optimization is typically for functions with bounded domain diameter. In unconstrained problems, previous works guarantee an asymptotic convergence rate without an…

Machine Learning · Computer Science 2023-10-05 Zijian Liu , Ta Duy Nguyen , Alina Ene , Huy L. Nguyen