Stable Conical Regularization by Constructible Dilating Cones with an Application to $L^{p}$-constrained Optimization Problems

Abstract

We study a convex constrained optimization problem that suffers from the lack of Slater-type constraint qualification. By employing a constructible representation of the constraint cone, we devise a new family of dilating cones and use it to introduce a family of regularized problems. We establish novel stability estimates for the regularized problems in terms of the regularization parameter. To show the feasibility and efficiency of the proposed framework, we present applications to some $L^{p}$-constrained least-squares problems.