Due to its versatility, copositive optimization receives increasing interest in the Operational
Research community, and is a rapidly expanding and fertile field of research. It is a special …

Copositive programming is a relatively young field in mathematical optimization. It can be
seen as a generalization of semidefinite programming, since it means optimizing over the …

Quadratic optimization lies at the very heart of many structural pattern recognition and
computer vision problems, such as graph matching, object recognition, image segmentation …

Copositive optimization is a quickly expanding scientific research domain with wide-spread
applications ranging from global nonconvex problems in engineering to NP-hard …

Recently, Kirkby et al. introduced a general and efficient nonparametric density estimation
procedure for local bases that is based on the statistical Galerkin method. However, the …

Projection-free block-coordinate methods avoid high computational cost per iteration, and at
the same time exploit the particular problem structure of product domains. Frank–Wolfe-like …

We propose a first-order interior-point method for linearly constrained smooth optimization
that unifies and extends first-order affine-scaling method and replicator dynamics method for …

A so-called Standard Bi-Quadratic Optimization Problem (StBQP) consists in minimizing a bi-
quadratic form over the Cartesian product of two simplices (so this is different from a Bi …

The aim of this paper is to present a review on the state-of-the-art related to quadratic
programming (QP) according to the methodology of Kitchenham and Charter. Our review …

Recently an affine scaling, interior point algorithm ASL was developed for box constrained
optimization problems with a single linear constraint (Gonzalez-Lima et al., SIAM J. Optim …