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: The method of nonlinear conjugate gradients (NCG) is widely used in practice for unconstrained optimization, but it satisfies weak complexity bounds at best when applied to smooth convex ...
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 ...
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 ...
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.
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 ...
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