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

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unpublished report, Columbia University, March 2009

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