A CONIC APPROACH FOR SEPARABLE CONVEX OPTIMIZATION

Geometric and l_p-norm optimization have been recently studied in the
framework of conic optimization, relying on the introduction of dedicated
convex cones. We present a generalization of these cones that leads to a
wide class of separable convex problems, study their duality properties and
investigate the development of self-concordant barriers applicable to this
class of problems.