Convex optimization for machine learning changho suh

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

While the mathematics of convex optimization has been studied for about a century, several related recent developments have stimulated new interest in the topic

The flrst is the recognition that interior-point methods, developed in the 1980stosolvelinearprogrammingproblems,canbeusedtosolveconvexoptimiza- tion problems as well