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 ...

This study introduced an efficient method for solving non-linear equations. Our approach enhances the traditional spectral conjugate gradient parameter, resulting in significant improvements in the ...

Adam is widely used in deep learning as an adaptive optimization algorithm, but it struggles with convergence unless the hyperparameter β2 is adjusted based on the specific problem. Attempts to fix ...

Abstract: Multigrid preconditioned conjugate gradient (MGPCG) is commonly used in high-performance computing (HPC) workloads. However, MGPCG is notoriously challenging to optimize since most of its ...

Having lived in several states, owning primary residences and investment properties, Josh Patoka uses his experience using mortgages and HELOCs to help first-time home buyers and home owners find the ...

MATLAB package of iterative regularization methods and large-scale test problems. This software is described in the paper "IR Tools: A MATLAB Package of Iterative Regularization Methods and ...

A class of finite step iterative methods, conjugate gradients, for the solution of an operator equation, is presented on this paper to solve electromagnetic scattering. The method of generalized ...

ABSTRACT: In this paper, three new hybrid nonlinear conjugate gradient methods are presented, which produce suf?cient descent search direction at every iteration. This property is independent of any ...

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 ...