Werner Schachinger

Think co(mpletely)positive ! Matrix properties, examples and a clustered bibliography on copositive optimization

Copositive optimization is a quickly expanding scientific research domain with wide-spread applications ranging from global nonconvex problems in engineering to NP-hard combinatorial optimization. It falls into the category of conic programming (optimizing a linear functional over a convex cone subject to linear constraints), namely the cone

On the variance of a class of inductive valuations of data structures for digital search

{\mathcal{C}}

New results on the cp-rank and related properties of co(mpletely )positive matrices

of all completely positive symmetric n × n matrices (which can be factorized into

Leland's Approach to Option Pricing: The Evolution of a Discontinuity

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Improved bounds for interatomic distance in Morse clusters

, where F is a rectangular matrix with no negative entry), and its dual cone