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Many combinatorial optimisation problems can be modelled as valued constraint satisfaction problems. In this paper, we present a polynomial-time algorithm solving the valued constraint satisfaction problem for a fixed number of variables…

Optimization and Control · Mathematics 2020-03-03 Manuel Bodirsky , Marcello Mamino , Caterina Viola

Consider a finite system of non-strict polynomial inequalities with solution set $S\subseteq\mathbb R^n$. Its Lasserre relaxation of degree $d$ is a certain natural linear matrix inequality in the original variables and one additional…

Algebraic Geometry · Mathematics 2018-11-30 Tom-Lukas Kriel , Markus Schweighofer

We study the convex relaxation of a polynomial optimization problem, maximizing a product of linear forms over the complex sphere. We show that this convex program is also a relaxation of the permanent of Hermitian positive semidefinite…

Optimization and Control · Mathematics 2021-01-21 Chenyang Yuan , Pablo A. Parrilo

A great variety of fundamental optimization and counting problems arising in computer science, mathematics and physics can be reduced to one of the following computational tasks involving polynomials and set systems: given an $m$-variate…

Data Structures and Algorithms · Computer Science 2016-11-15 Damian Straszak , Nisheeth K. Vishnoi

We show that the recent hierarchy of semidefinite programming relaxations based on non-commutative polynomial optimization and reduced density matrix variational methods exhibits an interesting paradox when applied to the bosonic case: even…

Quantum Physics · Physics 2013-02-19 M. Navascues , A. Garcia-Saez , A. Acin , S. Pironio , M. B. Plenio

In this paper we establish a connection between non-convex optimization methods for training deep neural networks and nonlinear partial differential equations (PDEs). Relaxation techniques arising in statistical physics which have already…

Machine Learning · Computer Science 2017-06-05 Pratik Chaudhari , Adam Oberman , Stanley Osher , Stefano Soatto , Guillaume Carlier

We propose an Extended Hybrid High-Order scheme for the Poisson problem with solution possessing weak singularities. Some general assumptions are stated on the nature of this singularity and the remaining part of the solution. The method is…

Numerical Analysis · Mathematics 2022-05-16 Liam Yemm

We consider stopping criteria that balance algebraic and discretization errors for the conjugate gradient algorithm applied to high-order finite element discretizations of Poisson problems. Firstly, we introduce a new stopping criterion…

Numerical Analysis · Mathematics 2024-08-06 Yichen Guo , Eric de Sturler , Tim Warburton

Biological and physical systems often exhibit distinct structures at different spatial/temporal scales. Persistent homology is an algebraic tool that provides a mathematical framework for analyzing the multi-scale structures frequently…

Algebraic Topology · Mathematics 2016-02-01 Jonathan Jaquette , Miroslav Kramár

Statistical inference problems arising within signal processing, data mining, and machine learning naturally give rise to hard combinatorial optimization problems. These problems become intractable when the dimensionality of the data is…

Statistical Mechanics · Physics 2017-04-27 Adel Javanmard , Andrea Montanari , Federico Ricci-Tersenghi

This work explores the tensor and combinatorial constructs underlying the linearised higher-order variational equations of a generic autonomous system along a particular solution. The main result of this paper is a compact yet explicit and…

Exactly Solvable and Integrable Systems · Physics 2015-02-11 Sergi Simon

We analyze integer linear programs which we obtain after discretizing two-dimensional subproblems arising from a trust-region algorithm for mixed integer optimal control problems with total variation regularization. We discuss NP-hardness…

Optimization and Control · Mathematics 2025-03-07 Paul Manns , Marvin Severitt

The study of combinatorial optimization problems with a submodular objective has attracted much attention in recent years. Such problems are important in both theory and practice because their objective functions are very general. Obtaining…

Data Structures and Algorithms · Computer Science 2016-11-11 Niv Buchbinder , Moran Feldman

Let X be the set of integer points in some polyhedron. We investigate the smallest number of facets of any polyhedron whose set of integer points is X. This quantity, which we call the relaxation complexity of X, corresponds to the smallest…

Combinatorics · Mathematics 2014-12-12 Volker Kaibel , Stefan Weltge

We consider optimal control problems for partial differential equations where the controls take binary values but vary over the time horizon, they can thus be seen as dynamic switches. The switching patterns may be subject to combinatorial…

Optimization and Control · Mathematics 2024-04-04 Christoph Buchheim , Alexandra Grütering , Christian Meyer

In this paper, we consider a bilevel polynomial optimization problem where the objective and the constraint functions of both the upper and the lower level problems are polynomials. We present methods for finding its global minimizers and…

Optimization and Control · Mathematics 2016-01-14 V. Jeyakumar , J. B. Lasserre , G. Li , T. S. Pham

We study a mixed integer linear program with m integer variables and k non-negative continuous variables in the form of the relaxation of the corner polyhedron that was introduced by Andersen, Louveaux, Weismantel and Wolsey [Inequalities…

Optimization and Control · Mathematics 2011-07-27 Amitabh Basu , Robert Hildebrand , Matthias Köppe

In recent years, semidefinite relaxations of common optimization problems in robotics have attracted growing attention due to their ability to provide globally optimal solutions. In many cases, it was shown that specific handcrafted…

Robotics · Computer Science 2024-10-03 Frederike Dümbgen , Connor Holmes , Ben Agro , Timothy D. Barfoot

We consider the high-dimensional discriminant analysis problem. For this problem, different methods have been proposed and justified by establishing exact convergence rates for the classification risk, as well as the l2 convergence results…

Machine Learning · Statistics 2013-06-28 Mladen Kolar , Han Liu

The recent results of An, Luan, and Yen [Differential stability in convex optimization via generalized polyhedrality. Vietnam J. Math. https://-doi.org/10.1007/s10013-024-00721-y] on differential stability of parametric optimization…

Optimization and Control · Mathematics 2024-12-17 Nguyen Dong Yen , Duong Thi Viet An , Vu Thi Huong , Nguyen Ngoc Luan