We are grateful for valuable suggestions and comments that we received from several colleagues r horst pm pardalos and nv thoai march 2000 preface to the first edition many recent advances in science economics and engineering rely on nu merical techniques for computing globally optimal solutions to corresponding optimization problems. Non convex optimization is now ubiquitous in machine learning while previously the focus was on convex relaxation methods now the emphasis is on being able to solve non convex problems directly it is not possible to find the global optimum of. Contribution this paper introduces the first distributed best response based algorithmic framework with provable con vergence for the nonconvex multi agent optimization in the general form 1 the crux of the framework is a novel convexification decomposition technique that hinges on our recent primal successive convex approximation sca. Suvrit sra mlmitedu trends in nonconvex optimization simons inst berkeley nonconvex problems are 2 nonconvex optimization problem with simple constraints question is global min of this problem 0 or not does there exist a subset of that sums to a
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