AbstractLet Rn denote the convex, compact set of all real n-by-n positive semidefinite matrices with main-diagonal entries equal to 1. We examine the extreme points of Rn focusing mainly on their rank. the principal result is that Rn contains extreme points of rank k if and only if k(k+1)⩽2n
AbstractLet Kn denote the closed convex set of all n-by-n positive semidefinite doubly stochastic ma...
A complete and simple parametrization of the set of extremal elements in the convex set of all corre...
AbstractLet Ms(x) ≔ {A ∈ Rn×n:A ⩾ 0, At = A, Ae = x}, where x is a vector with positive entries. We ...
AbstractLet Rn denote the convex, compact set of all real n-by-n positive semidefinite matrices with...
AbstractWe give a characterization for the extreme points of the convex set of correlation matrices ...
AbstractWe give a characterization for the extreme points of the convex set of correlation matrices ...
[[abstract]]An $n \times n$ complex Hermitian or real symmetric matrix is a correlation matrix if it...
AbstractLet Kn denote the closed convex set of all n-by-n positive semidefinite doubly stochastic ma...
AbstractLet G be an undirected graph on vertices {1,…,n}. Let M(G) be the convex cone of all positiv...
AbstractThis paper presents results about positive definite doubly stochastic matrices, in particula...
AbstractLet Kn be the convex set of n×n positive semidefinite doubly stochastic matrices. We show th...
AbstractThe set of all n×n double nonnegative (i.e., nonnegative and positive semidefinite) matrices...
A real symmetric matrix M is completely positive semidefinite if it admits a Gram representation by ...
A real symmetric matrix M is completely positive semidefinite if it admits a Gram representation by ...
An n× n matrix X is called completely positive semidefinite (cpsd) if there exist d× d Hermitian pos...
AbstractLet Kn denote the closed convex set of all n-by-n positive semidefinite doubly stochastic ma...
A complete and simple parametrization of the set of extremal elements in the convex set of all corre...
AbstractLet Ms(x) ≔ {A ∈ Rn×n:A ⩾ 0, At = A, Ae = x}, where x is a vector with positive entries. We ...
AbstractLet Rn denote the convex, compact set of all real n-by-n positive semidefinite matrices with...
AbstractWe give a characterization for the extreme points of the convex set of correlation matrices ...
AbstractWe give a characterization for the extreme points of the convex set of correlation matrices ...
[[abstract]]An $n \times n$ complex Hermitian or real symmetric matrix is a correlation matrix if it...
AbstractLet Kn denote the closed convex set of all n-by-n positive semidefinite doubly stochastic ma...
AbstractLet G be an undirected graph on vertices {1,…,n}. Let M(G) be the convex cone of all positiv...
AbstractThis paper presents results about positive definite doubly stochastic matrices, in particula...
AbstractLet Kn be the convex set of n×n positive semidefinite doubly stochastic matrices. We show th...
AbstractThe set of all n×n double nonnegative (i.e., nonnegative and positive semidefinite) matrices...
A real symmetric matrix M is completely positive semidefinite if it admits a Gram representation by ...
A real symmetric matrix M is completely positive semidefinite if it admits a Gram representation by ...
An n× n matrix X is called completely positive semidefinite (cpsd) if there exist d× d Hermitian pos...
AbstractLet Kn denote the closed convex set of all n-by-n positive semidefinite doubly stochastic ma...
A complete and simple parametrization of the set of extremal elements in the convex set of all corre...
AbstractLet Ms(x) ≔ {A ∈ Rn×n:A ⩾ 0, At = A, Ae = x}, where x is a vector with positive entries. We ...
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