An optimal subgradient algorithm for large-scale bound-constrained convex optimization

This paper shows that the OSGA algorithm — which uses first-order information to solve convex optimization problems with optimal complexity — can be used to efficiently solve arbitrary bound-constrained convex optimization problems. This is done by constructing an explicit method as well as an inexact scheme for solving the bound-constrained rational subproblem required by OSGA. … Read more