Conjugate gradient methods form a class of iterative algorithms that are highly effective for solving large‐scale unconstrained optimisation problems. They achieve efficiency by constructing ...

In this paper we present two algorithms for LC¹ unconstrained optimization problems which use the second order Dini upper directional derivative. These methods are simple and easy to perform. We ...

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.

In addition, the book includes an introduction to artificial neural networks, convex optimization, multi-objective optimization and applications of optimization in machine learning. About the Purdue ...