Pınar, M. Ç.Teboulle, M.2016-02-082016-02-0820060399-0559http://hdl.handle.net/11693/23775We consider the non-convex quadratic maximization problem subject to the ℓ1 unit ball constraint. The nature of the l1 norm structure makes this problem extremely hard to analyze, and as a consequence, the same difficulties are encountered when trying to build suitable approximations for this problem by some tractable convex counterpart formulations. We explore some properties of this problem, derive SDP-like relaxations and raise open questions.EnglishNon-convex quadratic optimizationL1-norm constraintSemidefinite programming relaxationDualityOn semidefinite bounds for maximization of a non-convex quadratic objective over the ℓ1 unit ballArticle10.1051/ro:20060231290-3868