Finding efficient and provable methods to solve non-convex optimization problems is an outstanding challenge in machine learning. A popular approach used to tackle non-convex problems is to use convex relaxation techniques to find a convex surrogate for the problem. Unfortunately, convex relaxations typically must be found on a problemby-problem basis. Thus… (More)