Smoothness of Subgradient Mappings and Its Applications in Parametric Optimization
Abstract
We demonstrate that the concept of strict proto-differentiability of subgradient mappings can play a similar role as smoothness of the gradient mapping of a function in the study of subgradient mappings of prox-regular functions. We then show that metric regularity and strong metric regularity are equivalent for a class of generalized equations when this condition is satisfied. For a class of composite functions, called C2-decomposable, we argue that strict proto-differentiability can be characterized via a simple relative interior condition. Leveraging this observation, we present a characterization of the continuous differentiability of the proximal mapping for this class of function via a certain relative interior condition. Applications to the study of strong metric regularity of the KKT system of a class of composite optimization problems are also provided.
Cite
@article{arxiv.2311.06026,
title = {Smoothness of Subgradient Mappings and Its Applications in Parametric Optimization},
author = {Nguyen T. V. Hang and Ebrahim Sarabi},
journal= {arXiv preprint arXiv:2311.06026},
year = {2024}
}