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 search ...

In this paper we test different conjugate gradient (CG) methods for solving largescale unconstrained optimization problems. The methods are divided in two groups: the first group includes five basic ...

Abstract: In order to address unconstrained optimization problems, conjugate gradient methods are frequently employed. When considering the unconstrained optimization issue, the accelerated conjugate ...

The nonlinear conjugate gradient method is a very useful technique for solving large scale minimization problems and has wide applications in many fields. In this paper, we present a new algorithm of ...

This is a preview. Log in through your library . Abstract In this paper, a family of three-term conjugate gradient methods is proposed to solve a large-scale unconstrained optimization problem. With ...

Abstract: Synthetic aperture radar (SAR) images are characterized by unique speckle noise, and maintaining image details while effectively reducing this noise has always been a challenging problem.

There are several optimization techniques available in PROC NLMIXED. You can choose a particular optimizer with the TECH=name option in the PROC NLMIXED statement. No algorithm for optimizing general ...

A clean, educational implementation of Trust Region Policy Optimization (TRPO) as described in the paper "Trust Region Policy Optimization" by Schulman et al. (2015). TRPO is a policy gradient method ...