Global Convergence Rate of Proximal Incremental Aggregated Gradient Methods
Global Convergence Rate of Proximal Incremental Aggregated Gradient Methods
We focus on the problem of minimizing the sum of smooth component functions (where the sum is strongly convex) and a nonsmooth convex function, which arises in regularized empirical risk minimization in machine learning and distributed constrained optimization in wireless sensor networks and smart grids. We consider solving this problem …