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A special type of multi-variate polynomial of degree 4, called the double well potential function, is studied. When the function is bounded from below, it has a very unique property that two or more local minimum solutions are separated by…

Optimization and Control · Mathematics 2014-10-23 Shu-Cherng Fang , David Yang Gao , Gang-Xuan Lin , Ruey-Lin Sheu , Wen-Xun Xing

Discrete Fenchel duality is one of the central issues in discrete convex analysis. The Fenchel-type min-max theorem for a pair of integer-valued M-natural-convex functions generalizes the min-max formulas for polymatroid intersection and…

Combinatorics · Mathematics 2021-12-07 Kazuo Murota , Akihisa Tamura

We present an adaptation of the MA-LBR scheme to the Monge-Amp{\`e}re equation with second boundary value condition, provided the target is a convex set. This yields a fast adaptive method to numerically solve the Optimal Transport problem…

Numerical Analysis · Mathematics 2018-07-19 Jean-David Benamou , Vincent Duval

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

Consider a polyhedral convex cone which is given by a finite number of linear inequalities. We investigate the problem to project this cone into a subspace and show that this problem is closely related to linear vector optimization: We…

Optimization and Control · Mathematics 2014-06-09 Andreas Löhne

In this technical note we provide a simple proof of Nehari's theorem on the optimal approximation by $H_\infty$ functions, based on convex duality.

Functional Analysis · Mathematics 2025-07-02 Cristian R. Rojas

We present an efficient, parallel, constrained optimization technique for approximating CAD curves with super-convergent rates. The optimization function is a disparity measure in terms of a piece-wise polynomial approximation and a curve…

Numerical Analysis · Mathematics 2022-12-05 Julia Docampo Sánchez

The purpose of the paper is to provide a characterization of the error of the best polynomial approximation of composite functions in weighted spaces. Such a characterization is essential for the convergence analysis of numerical methods…

Numerical Analysis · Mathematics 2023-08-14 Luisa Fermo , Concetta Laurita , Maria Grazia Russo

This paper addresses the study and applications of polyhedral duality of locally convex topological vector (LCTV) spaces. We first revisit the classical Rockafellar's proper separation theorem for two convex sets one which is polyhedral and…

Optimization and Control · Mathematics 2021-09-21 Dang Van Cuong , Boris Mordukhovich , Nguyen Mau Nam , Sandine Gary

We develop a general theory of convex duality for certain singular control problems, taking the abstract results by Kramkov and Schachermayer (1999) for optimal expected utility from nonnegative random variables to the level of optimal…

Optimization and Control · Mathematics 2014-07-30 Peter Bank , Helena Kauppila

We provide a solution method for the polyhedral convex set optimization problem, that is, the problem to minimize a set-valued mapping with polyhedral convex graph with respect to a set ordering relation which is generated by a polyhedral…

Optimization and Control · Mathematics 2024-09-27 Andreas Löhne

We study the solvability of the second boundary value problem for a class of highly singular fourth order equations of Monge-Amp\`ere type. They arise in the approximation of convex functionals subject to a convexity constraint using Abreu…

Analysis of PDEs · Mathematics 2021-05-05 Nam Q. Le , Bin Zhou

Coverings of convex bodies have emerged as a central component in the design of efficient solutions to approximation problems involving convex bodies. Intuitively, given a convex body $K$ and $\epsilon> 0$, a covering is a collection of…

Computational Geometry · Computer Science 2023-03-16 Sunil Arya , Guilherme D. da Fonseca , David M. Mount

In this paper, we consider solving a composite optimization problem with coupling constraints in a multi-agent network based on proximal gradient method. In this problem, all the agents jointly minimize the sum of individual cost functions…

Optimization and Control · Mathematics 2021-08-30 Jianzheng Wang , Guoqiang Hu

The curse of dimensionality in the realm of association rules is twofold. Firstly, we have the well known exponential increase in computational complexity with increasing item set size. Secondly, there is a \emph{related curse} concerned…

Artificial Intelligence · Computer Science 2018-05-16 Tom Hanika , Friedrich Martin Schneider , Gerd Stumme

This paper contributes to the study of optimal experimental design for Bayesian inverse problems governed by partial differential equations (PDEs). We derive estimates for the parametric regularity of multivariate double integration…

Numerical Analysis · Mathematics 2026-03-31 Vesa Kaarnioja , Claudia Schillings

This paper presents a study of generalized polyhedral convexity under basic operations on multifunctions. We address the preservation of generalized polyhedral convexity under sums and compositions of multifunctions, the domains and ranges…

Optimization and Control · Mathematics 2023-10-19 Nguyen Ngoc Luan , Nguyen Mau Nam , Nguyen Dong Yen

We derive approximation algorithms for the nonnegative matrix factorization problem, i.e. the problem of factorizing a matrix as the product of two matrices with nonnegative coefficients. We form convex approximations of this problem which…

Optimization and Control · Mathematics 2012-07-03 Vijay Krishnamurthy , Alexandre d'Aspremont

We consider minimization problems with bisubmodular objective functions. We propose valid inequalities, namely the poly-bimatroid inequalities, and provide a complete linear description of the convex hull of the epigraph of a bisubmodular…

Optimization and Control · Mathematics 2020-09-30 Qimeng Yu , Simge Kucukyavuz

While first-order optimization methods are usually designed to efficiently reduce the function value $f(x)$, there has been recent interest in methods efficiently reducing the magnitude of $\nabla f(x)$, and the findings show that the two…

Optimization and Control · Mathematics 2024-05-16 Jaeyeon Kim , Chanwoo Park , Asuman Ozdaglar , Jelena Diakonikolas , Ernest K. Ryu