An S-Hybridization Technique Using Two-Directional Optimization

In this paper, we study a recently established s-hybrid approach for generating gradient descent methods for solving optimization tasks. We present an s-hybrid variant of the accelerated double-direction method. The results obtained based on convergence analysis confirm the first-order consistency of the newly defined method on a set of strictly convex quadratic functions.