Local Convergence Rates of a Gauss-Newton Method for Convex Compositions

We discuss a Gauss-Newton methodology for minimizing convex compositions of smooth functions. We analyze current local rates of quadratic convergence when the subproblems are exactly solved and propose inexact methods that relax current sharpness assumptions while maintaining speeds of convergence.