Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1142473 | Operations Research Letters | 2012 | 5 Pages |
Abstract
We consider a special class of quadratic matrix optimization problems which often arise in applications. By exploiting the special structure of these problems, we derive a new semidefinite relaxation which, under mild assumptions, is proven to be tight for a larger number of constraints than could be achieved via a direct approach. We show the potential usefulness of these results when applied to robust least-squares and sphere-packing problems.
Related Topics
Physical Sciences and Engineering
Mathematics
Discrete Mathematics and Combinatorics
Authors
Amir Beck, Yoel Drori, Marc Teboulle,