This project implements a Single Layer Neural Network (SLNN) from scratch using Matlab. It focuses on the theoretical application and practical comparison of unconstrained optimization algorithms ...
In this paper the generalized Newton's method for LC¹ unconstrained optimization is investigated. This method is an extension of Newton's method for the smooth optimization. Some basic concepts are ...
The first laboratory work is devoted to optimization methods such as gradient descent and Newton's method. I implemented the methods themselves, the necessary oracles, as well as the linear search ...
Abstract: Quasi-Newton methods (QN) are very useful in finding the optimal solution to the unconstrained optimization problems. The updated Hessian approximations fulfill the equation on each ...
ABSTRACT: In this paper, we propose new variants of Newton’s method based on quadrature formula and power mean for solving nonlinear unconstrained optimization problems. It is proved that the order of ...
ABSTRACT: A hybrid method of the Polak-Ribière-Polyak (PRP) method and the Wei-Yao-Liu (WYL) method is proposed for unconstrained optimization pro- blems, which possesses the following properties: i) ...
Abstract: In this paper, we propose an efficient regular-ized quasi-Newton method for solving the unconstrained composite multiobjective optimization problem (UCMOP) where the objective functions are ...
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