Perturbation resilience of proximal gradient algorithm for composite objectives

In this paper, we study the perturbation resilience of a proximal gradient algorithm under the general Hilbert space setting. With the assumption that the error sequence is summable, we prove that the iterative sequence converges weakly to a solution of the composite optimization problem. We also show the bounded perturbation resilience of this iterative method and apply it to the lasso problem.