Abstract: The correlation matrix is a fundamental statistic that used in many fields. For example, GroupLens, a collaborative filtering system, uses the correlation between users for predictive ...

We study several variants of decomposing a symmetric matrix into a sum of a low-rank positive semidefinite matrix and a diagonal matrix. Such decompositions have applications in factor analysis and ...

Let K, K' be convex cones residing in finite-dimensional real vector spaces E, E'. An element in the tensor product E ⊗ E' is K ⊗ K'-separable if it can be represented as finite sum ∑_l x_l ⊗ x'_l ...

Characterising complex quantum systems is a vital task in quantum information science. Quantum tomography, the standard tool used for this purpose, uses a well-designed measurement record to ...

An illustration of a magnifying glass. An illustration of a magnifying glass.

Mathematics of Operations Research, Vol. 38, No. 3 (August 2013), pp. 569-590 (22 pages) Farkas' lemma is a fundamental result from linear programming providing linear certificates for infeasibility ...

We analyze two popular semidefinite programming relaxations for quadratically constrained quadratic programs with matrix variables. These relaxations are based on vector lifting and on matrix lifting; ...

Although of interest for over a century, most useful results concerning Euclidean distance matrices (EDMs) have appeared during the last thirty years, motivated by applications to the multidimensional ...