On the Convergence of Alternating Minimization for Convex Programming with Applications to Iteratively Reweighted Least Squares and Decomposition Schemes
This paper is concerned with the alternating minimization (AM) for solving convex minimization problems where the decision variables vector is split into two blocks. The objective function is a sum of a differentiable convex function and a separable (possible) nonsmooth extended real-valued convex function, and consequently constraints can be incorporated. We analyze the convergence rate … Read more