Eigenvalue techniques for proving bounds for convex objective, nonconvex programs
We describe techniques combining the S-lemma and computation of projected quadratics which experimentally yield strong bounds on the value of convex quadratic programs with nonconvex constraints Citationunpublished report, Columbia University, March 2009ArticleDownload View PDF