A Heuristic Fast Gradient Descent Method for Unimodal Optimization
George Anescu · Journal of Advances in Mathematics and Computer Science · 2018
The known gradient descent optimization methods applied to convex functions are using the gradient's magnitude in order to adaptively determine the current step size. The paper is presenting a new heuristic fast gradient descent (HFGD) approach, which uses the change in gradient'...
Open access
Research Article
10.9734/JAMCS/2018/39798