Jacobi-type algorithms for homogeneous polynomial optimization on Stiefel manifolds with applications to tensor approximations

Homogeneous Einstein metrics on Stiefel manifolds

A Stiefel manifold VkR n is the set of orthonormal k-frames inR, and it is diffeomorphic to the homogeneous space SO(n)/SO(n−k). We study SO(n)-invariant Einstein metrics on this space. We determine when the standard metric on SO(n)/SO(n−k) is Einstein, and we give an explicit solution to the Einstein equation for the space V2R.

Notes on Optimization on Stiefel Manifolds

Well-posedness of convex maximization problems on Stiefel manifolds and orthogonal tensor product approximations

Problems of best tensor product approximation of low orthogonal rank can be formulated as maximization problems on Stiefel manifolds. The functionals that appear are convex and weakly sequentially continuous. It is shown that such problems are always well-posed, even in the case of non-compact Stiefel manifolds. As a consequence, problems of finding a best orthogonal, strong orthogonal or compl...

Some Global Optimization Problems on Stiefel Manifolds

Optimization on Stiefel manifolds was discussed by Rapcsák in earlier papers, and some global optimization methods were considered and tested on Stiefel manifolds. In the paper, test functions are given with known global optimum points and their optimal function values. A restriction, which leads to a discretization of the problem is suggested, which results in a problem equivalent to the well-...

Approximation algorithms for homogeneous polynomial optimization with quadratic constraints

In this paper, we consider approximation algorithms for optimizing a generic multi-variate homogeneous polynomial function, subject to homogeneous quadratic constraints. Such optimization models have wide applications, e.g., in signal processing, magnetic resonance imaging (MRI), data training, approximation theory, and portfolio selection. Since polynomial functions are nonconvex in general, t...