Description
In this paper, we focus on solving convex minimization problem in the form of a summation of two convex functions in which one of them is Frecét differentiable. In order to solve this problem, we introduce a new accelerated viscosity forward-backward algorithm with a new linesearch technique. The proposed algorithm converges strongly to a solution of the problem without assuming that a gradient of the objective function is 
-Lipschitz continuous. As applications, we apply the proposed algorithm to classification problems and compare its performance with other algorithms mentioned in the literature.
