New accelerated fixed point algorithms with applications to regression and classification problems

Abstract

In this paper, we introduce and study a novel algorithm for finding a common fixed point of a countable family of nonexpansive mappings in Hilbert spaces. The main results obtained in this paper can be applied to solving regression and classification problems by using machine learning model.