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In the last decade, copositive formulations have been proposed for a variety of combinatorial optimization problems, for example the stability number (independence number). In this paper, we generalize this approach to infinite graphs and…

Optimization and Control · Mathematics 2016-10-12 Cristian Dobre , Mirjam Dür , Leonhard Frerick , Frank Vallentin

The kissing number of $\mathbb{R}^n$ is the maximum number of pairwise-nonoverlapping unit spheres that can simultaneously touch a central unit sphere. Mittelmann and Vallentin (2010), based on the semidefinite programming bound of Bachoc…

Optimization and Control · Mathematics 2016-09-19 Fabrício Caluza Machado , Fernando Mário de Oliveira Filho

We present an extension of known semidefinite and linear programming upper bounds for spherical codes. We apply the main result for the distance distribution of a spherical code and show that this method can work effectively In particular,…

Optimization and Control · Mathematics 2023-10-03 Oleg R. Musin

This chapter investigates the cone of copositive matrices, with a focus on the design and analysis of conic inner approximations for it. These approximations are based on various sufficient conditions for matrix copositivity, relying on…

Optimization and Control · Mathematics 2023-03-21 Luis Felipe Vargas , Monique Laurent

We apply the semidefinite programming approach developed in arxiv:math.MG/0608426 to obtain new upper bounds for codes in spherical caps. We compute new upper bounds for the one-sided kissing number in several dimensions where we in…

Metric Geometry · Mathematics 2009-02-06 Christine Bachoc , Frank Vallentin

Recently A. Schrijver derived new upper bounds for binary codes using semidefinite programming. In this paper we adapt this approach to codes on the unit sphere and we compute new upper bounds for the kissing number in several dimensions.…

Metric Geometry · Mathematics 2008-04-10 Christine Bachoc , Frank Vallentin

The kissing number in n-dimensional Euclidean space is the maximal number of non-overlapping unit spheres which simultaneously can touch a central unit sphere. Bachoc and Vallentin developed a method to find upper bounds for the kissing…

Optimization and Control · Mathematics 2019-11-07 Hans D. Mittelmann , Frank Vallentin

Postive semidefinite (PSD) cone is the cone of positive semidefinite matrices, and is the object of interest in semidefinite programming (SDP). A computational efficient approximation of the PSD cone is the $k$-PSD closure, $1 \leq k < n$,…

Optimization and Control · Mathematics 2021-06-07 Avinash Bhardwaj , Harshit Kothari , Vishnu Narayanan

This paper provides upper and lower bounds on the kissing number of congruent radius $r > 0$ spheres in hyperbolic $\mathbb{H}^n$ and spherical $\mathbb{S}^n$ spaces, for $n\geq 2$. For that purpose, the kissing number is replaced by the…

Combinatorics · Mathematics 2021-05-27 Maria Dostert , Alexander Kolpakov

The average kissing number of $\mathbb{R}^n$ is the supremum of the average degrees of contact graphs of packings of finitely many balls (of any radii) in $\mathbb{R}^n$. We provide an upper bound for the average kissing number based on…

Metric Geometry · Mathematics 2020-03-27 Maria Dostert , Alexander Kolpakov , Fernando Mário de Oliveira Filho

In this paper, we give some new lower bounds for the kissing number of $\ell_p$-spheres. These results improve the previous work due to Xu (2007). Our method is based on coding theory.

Metric Geometry · Mathematics 2022-07-21 Chengfei Xie , Gennian Ge

The maximum possible number of non-overlapping unit spheres that can touch a unit sphere in $n$ dimensions is called kissing number. The problem for finding kissing numbers is closely connected to the more general problems of finding bounds…

Metric Geometry · Mathematics 2015-07-15 Peter Boyvalenkov , Stefan Dodunekov , Oleg R. Musin

We construct near-optimal coresets for kernel density estimates for points in $\mathbb{R}^d$ when the kernel is positive definite. Specifically we show a polynomial time construction for a coreset of size $O(\sqrt{d}/\varepsilon\cdot…

Machine Learning · Computer Science 2019-04-15 Jeff M. Phillips , Wai Ming Tai

Interpolation and approximation of functionals with conditionally positive definite kernels is considered on sets of centers that are not determining for polynomials. It is shown that polynomial consistency is sufficient in order to define…

Numerical Analysis · Mathematics 2025-08-26 Oleg Davydov

Positive semidefinite (PSD) cone is the cone of positive semidefinite matrices, and is the object of interest in semidefinite programming (SDP). A computational efficient approximation of the PSD cone is the $k$-PSD closure, $1 \leq k < n$,…

Optimization and Control · Mathematics 2024-05-03 Avinash Bhardwaj , Vishnu Narayanan , Abhishek Pathapati

The authors in a previous paper devised certain subcones of the semidefinite plus nonnegative cone and showed that satisfaction of the requirements for membership of those subcones can be detected by solving linear optimization problems…

Optimization and Control · Mathematics 2021-06-01 Akihiro Tanaka , Akiko Yoshise

The paper introduces new sufficient conditions of strict positive definiteness for kernels on d-dimensional spheres which are not radially symmetric but possess specific coefficient structures. The results use the series expansion of the…

Numerical Analysis · Mathematics 2021-05-07 Martin Buhmann , Janin Jäger

We investigate the problem of finding inner ap-proximations of positive semidefinite (PSD) cones. We developa novel decomposition framework of the PSD cone by meansof conical combinations of smaller dimensional sub-cones. Weshow that many…

Optimization and Control · Mathematics 2021-10-01 Tianqi Zheng , James Guthrie , Enrique Mallada

The paper introduces a new characterisation of strictly positive definiteness for kernels on the 2-sphere without assuming the kernel to be radially (isotropic) or axially symmetric. The results use the series expansion of the kernel in…

Numerical Analysis · Mathematics 2022-05-06 Janin Jäger

We study a primal-dual interior point method specialized to clustered low-rank semidefinite programs requiring high precision numerics, which arise from certain multivariate polynomial (matrix) programs through sums-of-squares…

Optimization and Control · Mathematics 2025-02-24 Nando Leijenhorst , David de Laat
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