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Consider a sum of convex functions, where the only information known about each individual summand is the location of a minimizer. In this work, we give an exact characterization of the set of possible minimizers of the sum. Our results…

Optimization and Control · Mathematics 2024-03-11 Moslem Zamani , François Glineur , Julien M. Hendrickx

We prove Lieb type convexity and concavity results for trace functionals associated with positive operator monotone (decreasing) functions and certain monotone concave functions. This gives a partial generalization of Hiai's recent work on…

Functional Analysis · Mathematics 2021-06-18 Hans Henrich Neumann , Makoto Yamashita

This paper discusses a general and useful stability principle which, roughly speaking, says that given a uniformly continuous function defined on an arbitrary metric space, if the function is bounded on the constraint set and we slightly…

Optimization and Control · Mathematics 2020-09-04 Daniel Reem , Simeon Reich , Alvaro De Pierro

As an application of Brouwer's fixed-point theorem we prove that a continuously differentiable convex function with gradient of constant norm is an affine mapping. It is a first-order characterization of affine mappings among continuously…

Classical Analysis and ODEs · Mathematics 2025-11-10 Csaba Vincze

In discrete convex analysis, the scaling and proximity properties for the class of L$^\natural$-convex functions were established more than a decade ago and have been used to design efficient minimization algorithms. For the larger class of…

Combinatorics · Mathematics 2017-12-13 Satoko Moriguchi , Kazuo Murota , Akihisa Tamura , Fabio Tardella

We consider positive, integral-preserving linear operators acting on $L^1$ space, known as stochastic operators or Markov operators. We show that, on finite-dimensional spaces, any stochastic operator can be approximated by a sequence of…

Functional Analysis · Mathematics 2019-06-13 Shirin Moein , Rajesh Pereira , Sarah Plosker

Truncating the Fourier transform averaged by means of a generalized Hausdorff operator, we approximate the adjoint to that Hausdorff operator of the given function. We find the formulas for the rate of approximation in various metrics in…

Classical Analysis and ODEs · Mathematics 2019-07-31 Alberto Debernardi , Elijah Liflyand

The use of proximal point operators for optimization can be computationally expensive when the dimensionality of a function (i.e., the number of variables) is high. In this study, we sought to reduce the cost of calculating proximal point…

Optimization and Control · Mathematics 2023-12-06 Wen-Liang Hwang , Chang-Wei Yueh

We study operator log-convex functions on $(0,\infty)$, and prove that a continuous nonnegative function on $(0,\infty)$ is operator log-convex if and only if it is operator monotone decreasing. Several equivalent conditions related to…

Functional Analysis · Mathematics 2014-12-23 Tsuyoshi Ando , Fumio Hiai

Bernstein polynomials provide a constructive proof for the Weierstrass approximation theorem, which states that every continuous function on a closed bounded interval can be uniformly approximated by polynomials with arbitrary accuracy.…

Numerical Analysis · Mathematics 2023-07-24 Tiangang Cui , Friedrich Pillichshammer

The condition number of a differentiable convex function, namely the ratio of its smoothness to strong convexity constants, is closely tied to fundamental properties of the function. In particular, the condition number of a quadratic convex…

Optimization and Control · Mathematics 2020-04-21 David H. Gutman , Javier F. Pena

We derive normal approximation results for a class of stabilizing functionals of binomial or Poisson point process, that are not necessarily expressible as sums of certain score functions. Our approach is based on a flexible notion of the…

Probability · Mathematics 2022-10-20 Zhaoyang Shi , Krishnakumar Balasubramanian , Wolfgang Polonik

In this paper, approximate convexity and approximate midconvexity properties, called $\varphi$-convexity and $\varphi$-midconvexity, of real valued function are investigated. Various characterizations of $\varphi$-convex and…

Classical Analysis and ODEs · Mathematics 2012-11-21 Judit Makó , Zsolt Páles

We analyse the convergence of the proximal gradient algorithm for convex composite problems in the presence of gradient and proximal computational inaccuracies. We derive new tighter deterministic and probabilistic bounds that we use to…

Optimization and Control · Mathematics 2022-03-07 Anis Hamadouche , Yun Wu , Andrew M. Wallace , Joao F. C. Mota

Matrix versions of some basic convexity inequalities are given. Further results on the same topic are proved in the recent papers on arxiv: 1. Hermitian operators and convex functions, 2. A concavity inequality for symmetric norms, 3.…

Functional Analysis · Mathematics 2007-05-23 Jean-Christophe Bourin

We study the filtering of the perspective of a regular operator map of several variables through a completely positive linear map. By this method we are able to extend known operator inequalities of two variables to several variables; with…

Mathematical Physics · Physics 2017-04-05 Frank Hansen

We construct a Lipschitz truncation which approximates functions of bounded variation in the area-strict metric. The Lipschitz truncation changes the original function only on a small set similar to Lusin's theorem. Previous results could…

Analysis of PDEs · Mathematics 2019-08-29 Dominic Breit , Lars Diening , Franz Gmeineder

We present results about minimization of convex functionals defined over a finite set of vectors in a finite dimensional Hilbert space, that extend several known results for the Benedetto-Fickus frame potential. Our approach depends on…

Functional Analysis · Mathematics 2007-10-08 Pedro Massey , Mariano Ruiz

It was already known that a p-adic, locally Lipschitz continuous semi-algebraic function is piecewise Lipschitz continuous, where the pieces can be taken semi-algebraic. We prove that if the function has locally Lipschitz constant 1, then…

Logic · Mathematics 2010-10-01 Raf Cluckers , Immanuel Halupczok

Approximations of optimization problems arise in computational procedures and sensitivity analysis. The resulting effect on solutions can be significant, with even small approximations of components of a problem translating into large…

Optimization and Control · Mathematics 2022-08-10 Johannes O. Royset