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We develop an algorithmic theory of convex optimization over discrete sets. Using a combination of algebraic and geometric tools we are able to provide polynomial time algorithms for solving broad classes of convex combinatorial…

Optimization and Control · Mathematics 2009-01-24 Shmuel Onn

Obtaining the inverse of a large symmetric positive definite matrix $\mathcal{A}\in\mathbb{R}^{p\times p}$ is a continual challenge across many mathematical disciplines. The computational complexity associated with direct methods can be…

Numerical Analysis · Mathematics 2025-09-03 Ann Paterson , Jennifer Pestana , Victorita Dolean

We consider the following problem: Given a rational matrix $A \in \setQ^{m \times n}$ and a rational polyhedron $Q \subseteq\setR^{m+p}$, decide if for all vectors $b \in \setR^m$, for which there exists an integral $z \in \setZ^p$ such…

Optimization and Control · Mathematics 2008-01-29 Friedrich Eisenbrand , Gennady Shmonin

The paper provides a connection between Commutative Algebra and Integer Programming and contains two parts. The first one is devoted to the asymptotic behavior of integer programs with a fixed cost linear functional and the constraint sets…

Commutative Algebra · Mathematics 2020-11-03 Le Tuan Hoa

Linear programming describes the problem of optimising a linear objective function over a set of constraints on its variables. In this paper we present a solver for linear programs implemented in the proof assistant Isabelle/HOL. This…

Logic in Computer Science · Computer Science 2024-03-29 Julian Parsert

Integer programs with m constraints are solvable in pseudo-polynomial time in $\Delta$, the largest coefficient in a constraint, when m is a fixed constant. We give a new algorithm with a running time of $O(\sqrt{m}\Delta)^{2m} + O(nm)$,…

Data Structures and Algorithms · Computer Science 2022-07-27 Klaus Jansen , Lars Rohwedder

In bi-objective integer optimization the optimal result corresponds to a set of non-dominated solutions. We propose a generic bi-objective branch-and-bound algorithm that uses a problem-independent branching rule exploiting available…

Data Structures and Algorithms · Computer Science 2018-09-19 Sophie N. Parragh , Fabien Tricoire

A very classical subject in Commutative Algebra is the Invariant Theory of finite groups. In our work on 3-dimensional topology (S. King, Ideal Turaev-Viro invariants. To appear in Top. Appl.), we found certain examples of group actions on…

Commutative Algebra · Mathematics 2007-05-23 Simon A. King

We consider a scalar objective minimization problem over the solution set of another optimization problem. This problem is known as simple bilevel optimization problem and has drawn a significant attention in the last few years. Our inner…

Optimization and Control · Mathematics 2018-09-18 Yekini Shehu , Phan Tu Vuong , Alain Zemkoho

This paper considers the problem of calculating the matrix multiplication of two massive matrices $\mathbf{A}$ and $\mathbf{B}$ distributedly. We provide a modulo technique that can be applied to coded distributed matrix multiplication…

Information Theory · Computer Science 2023-09-20 Zhiquan Tan , Dingli Yuan , Zihao Wang , Zhongyi Huang

In this paper, we propose a mixed-binary convex quadratic programming reformulation for the box-constrained nonconvex quadratic integer program and then implement IBM ILOG CPLEX 12.6 to solve the new model. Computational results demonstrate…

Optimization and Control · Mathematics 2014-01-24 Yong Xia , Ying-Wei Han

We propose a new more efficient method for the computation of two-sided Gr\"obner bases of ideals and bimodules shifting the problem to the enveloping algebra. Arising from the ideas this method involves, we introduce the notion of…

Rings and Algebras · Mathematics 2016-08-16 M. García Román , S. García Román

Block matrix structure is commonly arising is various physics and engineering applications. There are various advantages in preserving the blocks structure while computing the inversion of such partitioned matrices. In this context, using…

Numerical Analysis · Mathematics 2023-11-22 R. Thiru Senthil

The paper addresses the study and applications of a broad class of extended-real-valued functions, known as optimal value or marginal functions, which are frequently appeared in variational analysis, parametric optimization, and a variety…

Optimization and Control · Mathematics 2025-02-05 Le Phuoc Hai , Felipe Lara , Boris S. Mordukhovich

Inverse optimization, determining parameters of an optimization problem that render a given solution optimal, has received increasing attention in recent years. While significant inverse optimization literature exists for convex…

Optimization and Control · Mathematics 2021-09-02 Merve Bodur , Timothy C. Y. Chan , Ian Yihang Zhu

In contrast with many other convex optimization classes, state-of-the-art semidefinite programming solvers are yet unable to efficiently solve large scale instances. This work aims to reduce this scalability gap by proposing a novel…

Optimization and Control · Mathematics 2018-12-20 Mario Souto , Joaquim D. Garcia , Alvaro Veiga

Matrices resulting from the discretization of a kernel function, e.g., in the context of integral equations or sampling probability distributions, can frequently be approximated by interpolation. In order to improve the efficiency, a…

Numerical Analysis · Mathematics 2021-12-10 Steffen Börm

In this paper we present an efficient algorithm for bivariate interpolation, which is based on the use of the partition of unity method for constructing a global interpolant. It is obtained by combining local radial basis function…

Numerical Analysis · Mathematics 2014-08-04 Roberto Cavoretto

We follow up on the idea of Lars Arge to rephrase the Reduce and Apply procedures of Binary Decision Diagrams (BDDs) as iterative I/O-efficient algorithms. We identify multiple avenues to simplify and improve the performance of his proposed…

Data Structures and Algorithms · Computer Science 2026-03-25 Steffan Christ Sølvsten , Jaco van de Pol , Anna Blume Jakobsen , Mathias Weller Berg Thomasen

Submodular function maximization is a critical building block for diverse tasks, such as document summarization, sensor placement, and image segmentation. Yet its practical utility is often limit by the $O(knd^2)$ computational bottleneck.…

Machine Learning · Computer Science 2026-01-29 Boyu Liu , Lianke Qin , Zhao Song , Yitan Wang , Jiale Zhao
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