The Handbook of Linear Algebra provides comprehensive coverage of linear algebra
concepts, applications, and computational software packages in an easy-to-use handbook …

Semidefinite programming has been described as linear programming for the year 2000. It is
an exciting new branch of mathematical programming, due to important applications in …

Given a partial symmetric matrix A with only certain elements specified, the Euclidean
distance matrix completion problem (EDMCP) is to find the unspecified elements of A that …

We discuss several different search directions which can be used in primal-dual interior-
point methods for semidefinite programming problems and investigate their theoretical …

We study Semidefinite Programming, SDP, relaxations for Sensor Network Localization,
SNL, with anchors and with noisy distance information. The main point of the paper is to …

In this paper, we survey the most recent methods that have been developed for the solution
of semidefinite programs. We first concentrate on the methods that have been primarily …

A partial pre-distance matrix A is a matrix with zero diagonal and with certain elements fixed
to given nonnegative values; the other elements are considered free. The Euclidean …

In semidefinite programming a proposed optimal solution may be quite poor in spite of
having sufficiently small residual in the optimality conditions. This issue may be framed in …

Semidefinite programming (SDP) is currently one of the most active areas of research in
optimization. SDP has attracted researchers from a wide variety of areas because of its …

Semidefinite programs have recently turned out to be a powerful tool for approximating
integer problems. To survey the development in this area over the last few years, the …