A Novel algorithm for convex bi-level optimization problems in hilbert spaces with applications

Abstract

In this thesis, we present a new accelerated algorithm for solving convex bi-level optimization problems in Hilbert spaces and analyse convergence behavior of the proposed algorithms. We prove the strong convergence theorems of the proposed algorithms under some suitable conditions. As an application, we apply our main results to solve some data classification problems.