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Convexity and convex functions play an important role in theoretical physics. To initiate a study of the possible uses of convex functions in General Relativity, we discuss the consequences of a spacetime $(M,g_{\mu \nu})$ or an initial…

Differential Geometry · Mathematics 2017-02-21 Gary W. Gibbons , Akihiro Ishibashi

The notion of ordinal concavity of utility functions has recently been considered by Hafalir, Kojima, Yenmez, and Yokote in economics while there exist earlier related works in discrete optimization and operations research. In the present…

Combinatorics · Mathematics 2024-11-14 Satoru Fujishige , Fuhito Kojima , Koji Yokote

We explore the relationship between convex and subharmonic functions on discrete sets. Our principal concern is to determine the setting in which a convex function is necessarily subharmonic. We initially consider the primary notions of…

Combinatorics · Mathematics 2014-06-25 Matthew Burke , Tony Perkins

We define a generalization of convex functions, which we call $\delta$-convex functions, and show they must satisfy interior H\"older and $W^{1,p}$ estimates. As an application, we consider solutions of a certain class of fully nonlinear…

Differential Geometry · Mathematics 2007-05-23 Matthew Gursky , Jeff Viaclovsky

In this article we utilise abstract convexity theory in order to unify and generalize many different concepts from nonsmooth analysis. We introduce the concepts of abstract codifferentiability, abstract quasidifferentiability and abstract…

Optimization and Control · Mathematics 2018-10-03 M. V. Dolgopolik

We construct an example of a smooth convex function on the plane with a strict minimum at zero, which is real analytic except at zero, for which Thom's gradient conjecture fails both at zero and infinity. More precisely, the gradient orbits…

Dynamical Systems · Mathematics 2021-09-02 Aris Daniilidis , Mounir Haddou , Olivier Ley

A complete classification of continuous, dually epi-translation invariant, and rotation equivariant valuations on convex functions is established. This characterizes the recently introduced functional Minkowski vectors, which naturally…

Metric Geometry · Mathematics 2025-04-24 Mohamed A. Mouamine , Fabian Mussnig

We introduce new global and local inexact oracle concepts for a wide class of convex functions in composite convex minimization. Such inexact oracles naturally come from primal-dual framework, barrier smoothing, inexact computations of…

Optimization and Control · Mathematics 2020-02-25 Tianxiao Sun , Ion Necoara , Quoc Tran-Dinh

We present a closed-form finite-dimensional projection method for regularizing a function defined by a discrete set of measurement data, which have been contaminated by random, zero mean errors, and for estimating the derivative and…

Numerical Analysis · Mathematics 2018-05-28 Timothy J. Burns , Bert W. Rust

This work is devoted to a systematic study of symplectic convexity for integrable Hamiltonian systems with elliptic and focus-focus singularities. A distinctive feature of these systems is that their base spaces are still smooth manifolds…

Symplectic Geometry · Mathematics 2018-09-18 Tudor Ratiu , Christophe Wacheux , Nguyen Tien Zung

We study the convolution of functions of the form \[ f_\alpha (z) := \dfrac{\left( \frac{1 + z}{1 - z} \right)^\alpha - 1}{2 \alpha}, \] which map the open unit disk of the complex plane onto polygons of 2 edges when $\alpha\in(0,1)$. We…

Complex Variables · Mathematics 2024-10-29 Martin Chuaqui , Rodrigo Hernández , Adrián Llinares , Alejandro Mas

We consider the space of convex functions defined in the Euclidean $n$-dimensional space, which are lower semi-continuous and tend to infinity at infinity. We study real-valued valuations defined on this space of functions, which are…

Metric Geometry · Mathematics 2015-08-04 L. Cavallina , A. Colesanti

The deprojection of axisymmetric density distributions is generally indeterminate to within the addition of certain axisymmetric distributions (konus densities) that are invisible in projection. The known class of konus densities is…

Astrophysics · Physics 2015-06-24 C. S. Kochanek , G. B. Rybicki

Mixed volumes, which are the polarization of volume with respect to the Minkowski addition, are fundamental objects in convexity. In this note we announce the construction of mixed integrals, which are functional analogs of mixed volumes.…

Functional Analysis · Mathematics 2013-02-05 Vitali Milman , Liran Rotem

In this article, we further explore convex functions by revealing new bounds, resulting from stronger convexity behavior. In particular, we define the so called radical convex functions and study their properties. We will see that such…

Functional Analysis · Mathematics 2020-10-13 Mohammad Sababheh , Hamid Reza Moradi

The convex feasibility problem (CFP) is to find a feasible point in the intersection of finitely many convex and closed sets. If the intersection is empty then the CFP is inconsistent and a feasible point does not exist. However,…

Optimization and Control · Mathematics 2018-04-27 Yair Censor , Maroun Zaknoon

In this paper we give an integral representation of an $n$-convex function $f$ in general case without additional assumptions on function $f$. We prove that any $n$-convex function can be represented as a sum of two $(n+1)$-times monotone…

Classical Analysis and ODEs · Mathematics 2010-08-17 Teresa Rajba

We study some methods of subgradient projections for solving a convex feasibility problem with general (not necessarily hyperplanes or half-spaces) convex sets in the inconsistent case and propose a strategy that controls the relaxation…

Optimization and Control · Mathematics 2010-09-21 Dan Butnariu , Yair Censor , Pini Gurfil , Ethan Hadar

In this paper, we explore a broad class of constrained saddle point problems with a bilevel structure, wherein the upper-level objective function is nonconvex-concave and smooth over compact and convex constraint sets, subject to a strongly…

Optimization and Control · Mathematics 2025-03-31 Mohammad Mahdi Ahmadi , Erfan Yazdandoost Hamedani

Convolution is conventionally defined as a linear operation on functions of one or more variables which commutes with shifts. Group convolution generalizes the concept to linear operations on functions of group elements representing more…

Computer Vision and Pattern Recognition · Computer Science 2022-03-16 Xinhua Zhang , Lance R. Williams
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