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Related papers: More convex functions by Artin`s method

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In this paper, we obtain some new inequalities for functions whose second derivatives' absolute value is s-convex and log-convex. Also, we give some applications for numerical integration.

Classical Analysis and ODEs · Mathematics 2014-09-04 Ahmet Ocak Akdemir , Merve Avci Ardic , M. Emin Özdemir

In this paper, a new identity for convex functions is derived. A consequence of the identity is that we can derive new estimates for the remainder term of the midpoint, trapezoid, and Simpson formulae for functions whose derivatives in…

Classical Analysis and ODEs · Mathematics 2012-07-31 Imdat Iscan

We derive two types of representation results for increasing convex functionals in terms of countably additive measures. The first is a max-representation of functionals defined on spaces of real-valued continuous functions and the second a…

Functional Analysis · Mathematics 2021-03-30 Patrick Cheridito , Michael Kupper , Ludovic Tangpi

Let $S$ be a semigroup. Our main results is that we describe the complex-valued solutions of the following functional equations \[g(x\sigma (y)) = g(x)g(y)+f(x)f(y),\ x,y\in S,\] \[f(x\sigma (y)) = f(x)g(y)+f(y)g(x),\ x,y\in S,\] and…

Functional Analysis · Mathematics 2023-02-22 Youssef Aserrar , Elhoucien Elqorachi

This note deals with certain properties of convex functions. We provide results on the convexity of the set of minima of these functions, the behaviour of their subgradient set under restriction, and optimization of these functions over an…

Optimization and Control · Mathematics 2017-03-21 Miel Sharf , Daniel Zelazo

Two kinds of infinite product representations for Vign\'eras multiple gamma function are presented. As an application of these formulas, a multiplication formula for the function is derived.

Classical Analysis and ODEs · Mathematics 2007-05-23 Michitomo Nishizawa

We establish a general principle which states that regularizing an inverse problem with a convex function yields solutions which are convex combinations of a small number of atoms. These atoms are identified with the extreme points and…

Optimization and Control · Mathematics 2018-11-27 Claire Boyer , Antonin Chambolle , Yohann De Castro , Vincent Duval , Frédéric De Gournay , Pierre Weiss

Extending classical results on polytopal approximation of convex bodies, we derive asymptotic formulas for the weighted approximation of smooth convex functions by piecewise affine convex functions as the number of their facets tends to…

Optimization and Control · Mathematics 2025-10-01 Fernanda M. Baêta

We consider scalar equilibrium problems governed by a bifunction in a finite-dimensional framework. By using classical arguments in Convex Analysis, we show that under suitable generalized convexity assumptions imposed on the bifunction,…

Optimization and Control · Mathematics 2024-01-02 Valerian-Alin Fodor , Nicolae Popovici

Approximate solutions to functional evolution equations are constructed through a combination of series and conjugation methods, and relative errors are estimated. The methods are illustrated, both analytically and numerically, by…

Mathematical Physics · Physics 2015-03-19 Thomas Curtright , Xiang Jin , Cosmas Zachos

Convergence rates results for variational regularization methods typically assume the regularization functional to be convex. While this assumption is natural for scalar-valued functions, it can be unnecessarily strong for vector-valued…

Optimization and Control · Mathematics 2017-09-13 Clemens Kirisits , Otmar Scherzer

We discuss the following question: For a function f of two or more variables which is convex in the directions of coordinate axes, how can its trace g(x) = f(x, x, ..., x) look like? In the two-dimensional case, we provide some necessary…

Optimization and Control · Mathematics 2017-10-24 Ondřej Kurka , Dušan Pokorný

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

The study of convex functions - in particular, of their optimization (really minimization) is one of the most important fields of applied mathematics. Convexity seems to be one of those incredibly well-chosen hypotheses which is just…

Optimization and Control · Mathematics 2026-03-11 Eigil Fjeldgren Rischel

Given a semigroup $S$ equipped with an involutive automorphism $\sigma$, we determine the complex-valued solutions $f,g,h$ of the functional equation \begin{equation*}f(x\sigma(y))=f(x)g(y)+g(x)f(y)+h(x)h(y),\,\,x,y\in S,\end{equation*} in…

General Mathematics · Mathematics 2023-12-12 Omar Ajebbar , Elhoucien Elqorach

We consider solvable matrix models. We generalize Harish-Chandra-Itzykson-Zuber and certain other integrals (Gross-Witten integral and integrals over complex matrices) using the notion of tau function of matrix argument. In this case one…

Mathematical Physics · Physics 2007-05-23 A. Yu. Orlov

A method to calculate exact Green's functions on lattices in various dimensions is presented. Expressions in terms of generalized hypergeometric functions in one or more variables are obtained for various examples by relating the resolvent…

Mathematical Physics · Physics 2014-09-30 Koushik Ray

We show that the large Cartesian powers of any graph have log-concave valencies with respect to a ffxed vertex. We show that the series of valencies of distance regular graphs is log-concave, thus improving on a result of (Taylor,…

Combinatorics · Mathematics 2025-01-22 Minjia Shi , Lu Wang , Patrick Sole

By treating the multiple argument identity of the logarithm of the Gamma function as a functional equation, we obtain a curious infinite product representation of the $sinc$ function in terms of the cotangent function. This result is…

General Mathematics · Mathematics 2023-06-12 Michael Milgram

We consider the problem of predicting the covariance of a zero mean Gaussian vector, based on another feature vector. We describe a covariance predictor that has the form of a generalized linear model, i.e., an affine function of the…

Machine Learning · Statistics 2021-02-01 Shane Barratt , Stephen Boyd
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