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 ...

Abstract: Backpropagation neural networks are commonly utilized to solve complicated issues in various disciplines. However, optimizing their settings remains a significant task. Traditional ...

Abstract: This paper presents a new three-term hybrid conjugate gradient projection method for handling large-scale convex-constrained nonlinear monotone equations that are prevalent in fields such as ...

ABSTRACT: Three PRP-type direct search methods for unconstrained optimization are presented. The methods adopt three kinds of recently developed descent conjugate gradient methods and the idea of ...

GPU-accelerated linear solvers based on the conjugate gradient (CG) method, supporting NVIDIA and AMD GPUs with GPU-aware MPI, NCCL, RCCL or NVSHMEM ...

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 ...

Below, you will find information about software developed by the Center, as well as download links. Disclaimer: This software is provided without any expressed or implied warranty. In particular, ...

The following repo contains implementations of various optimization algorithms in Julia. I created this project to be better understand how these algortihms work and how they could be implemented in ...