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The effectiveness of projection methods for solving systems of linear inequalities is investigated. It is shown that they have a computational advantage over some alternatives and that this makes them successful in real-world applications.…

Optimization and Control · Mathematics 2009-12-23 Y. Censor , W. Chen , P. L. Combettes , R. Davidi , G. T. Herman

Extended real-valued functions are often used in optimization theory, but in different ways for infimum problems and for supremum problems. We present an approach to extended real-valued functions that works for all types of problems and…

Optimization and Control · Mathematics 2018-06-11 Petra Weidner

In this paper we present equivalence results for several types of unbounded operator functions. A generalization of the concept equivalence after extension is introduced and used to prove equivalence and linearization for classes of…

Functional Analysis · Mathematics 2017-09-27 Christian Engström , Axel Torshage

We characterize all linear operators on finite or infinite-dimensional spaces of univariate real polynomials preserving the sets of elliptic, positive, and non-negative polynomials, respectively. This is done by means of Fischer-Fock…

Classical Analysis and ODEs · Mathematics 2009-02-04 Julius Borcea

This document introduces a strategy to solve linear optimization problems. The strategy is based on the bounding condition each constraint produces on each one of the problem's dimension. The solution of a linear optimization problem is…

Optimization and Control · Mathematics 2018-09-24 Gerardo L. Febres

We review several (and provide new) results on the theory of moments, sums of squares and basic semi-algebraic sets when convexity is present. In particular, we show that under convexity, the hierarchy of semidefinite relaxations for…

Optimization and Control · Mathematics 2008-12-04 Jean B. Lasserre

Quadratic-support functions [Aravkin, Burke, and Pillonetto; J. Mach. Learn. Res. 14(1), 2013] constitute a parametric family of convex functions that includes a range of useful regularization terms found in applications of convex…

Optimization and Control · Mathematics 2018-08-23 Michael P. Friedlander , Gabriel Goh

Polynomial approximations of functions are widely used in scientific computing. In certain applications, it is often desired to require the polynomial approximation to be non-negative (resp. non-positive), or bounded within a given range,…

Numerical Analysis · Mathematics 2024-11-12 Yuan Chen , Dongbin Xiu , Xiangxiong Zhang

The motivation of this paper is the development of an optimisation method for solving optimisation problems appearing in Chebyshev rational and generalised rational approximation problems, where the approximations are constructed as ratios…

Optimization and Control · Mathematics 2020-11-06 R. Díaz Millán , Nadezda Sukhorukova , Julien Ugon

We consider the homogenized linear feasibility problem, to find an $x$ on the unit sphere, satisfying $n$ line ar inequalities $a_i^Tx\ge 0$. To solve this problem we consider the centers of the insphere of spherical simpl ices, whose…

Optimization and Control · Mathematics 2007-05-23 Ulrich Betke

Convexification based on convex envelopes is ubiquitous in the non-linear optimization literature. Thanks to considerable efforts of the optimization community for decades, we are able to compute the convex envelopes of a considerable…

Optimization and Control · Mathematics 2022-10-17 Javiera Barrera , Eduardo Moreno , Gonzalo Muñoz

The article deals with operations defined on convex polyhedra or polyhedral convex functions. Given two convex polyhedra, operations like Minkowski sum, intersection and closed convex hull of the union are considered. Basic operations for…

Optimization and Control · Mathematics 2018-07-17 Daniel Ciripoi , Andreas Löhne , Benjamin Weißing

We introduce sequences of functions orthogonal on a finite interval: proper orthogonal rational functions, orthogonal exponential functions, orthogonal logarithmic functions, and transmuted orthogonal polynomials

Classical Analysis and ODEs · Mathematics 2023-01-20 Vladimir S. Chelyshkov

We study a family of (potentially non-convex) constrained optimization problems with convex composite structure. Through a novel analysis of non-smooth geometry, we show that proximal-type algorithms applied to exact penalty formulations of…

Optimization and Control · Mathematics 2019-03-04 Yu Bai , John Duchi , Song Mei

When computing bounds, spatial branch-and-bound algorithms often linearly outer approximate convex relaxations for non-convex expressions in order to capitalize on the efficiency and robustness of linear programming solvers. Considering…

Optimization and Control · Mathematics 2025-12-22 William R. Strahl , Arvind U. Raghunathan , Nikolaos V. Sahinidis , Chrysanthos E. Gounaris

We are interested in the fast computation of the exact value of integrals of polynomial functions over convex polyhedra. We present speed ups and extensions of the algorithms presented in previous work. We present the new software…

Metric Geometry · Mathematics 2013-12-30 Jesus De Loera , Brandon Dutra , Matthias Koeppe , Stanislav Moreinis , Gregory Pinto , Jianqiu Wu

In this paper, we study a solution approach for set optimization problems with respect to the lower set less relation. This approach can serve as a base for numerically solving set optimization problems by using established solvers from…

Optimization and Control · Mathematics 2021-07-27 Gabriele Eichfelder , Ernest Quintana , Stefan Rocktäschel

Left-right and conjugation actions on matrix tuples have received considerable attention in theoretical computer science due to their connections with polynomial identity testing, group isomorphism, and tensor isomorphism. In this paper, we…

Data Structures and Algorithms · Computer Science 2024-09-20 Youming Qiao , Xiaorui Sun

We consider the factorization of a rectangular matrix $X $ into a positive linear combination of rank-one factors of the form $u v^\top$, where $u$ and $v$ belongs to certain sets $\mathcal{U}$ and $\mathcal{V}$, that may encode specific…

Machine Learning · Computer Science 2013-09-13 Francis Bach

We present a new algorithm to decompose generic spinor polynomials into linear factors. Spinor polynomials are certain polynomials with coefficients in the geometric algebra of dimension three that parametrize rational conformal motions.…

Rings and Algebras · Mathematics 2023-11-14 Zijia Li , Hans-Peter Schröcker , Johannes Siegele
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