Results 11 to 20 of about 124,946 (301)

THE NEW RANK ONE CLASS FOR UNCONSTRAINED PROBLEMS SOLVING

open access: yesScience Journal of University of Zakho, 2023
One of the most well-known methods for unconstrained problems is the quasi-Newton approach, iterative solutions. The great precision and quick convergence of the quasi-Newton methods are well recognized. In this work, the new algorithm for the symmetric
Ahmed Mustafa
doaj   +1 more source

Matrix Transformations and Quasi-Newton Methods [PDF]

open access: yesInternational Journal of Mathematics and Mathematical Sciences, 2007
We first recall some properties of infinite tridiagonal matrices considered as matrix transformations in sequence spaces of the formssξ,sξ∘,sξ(c), orlp(ξ). Then, we give some results on the finite section method for approximating a solution of an infinite linear system.
Boubakeur Benahmed   +2 more
openaire   +4 more sources

Correlation and realization of quasi-Newton methods of absolute optimization [PDF]

open access: yesКомпьютерные исследования и моделирование, 2016
Newton and quasi-Newton methods of absolute optimization based on Cholesky factorization with adaptive step and finite difference approximation of the first and the second derivatives.
Anastasiya Borisovna Sviridenko   +1 more
doaj   +1 more source

On the Convergence Rate of Quasi-Newton Methods on Strongly Convex Functions with Lipschitz Gradient

open access: yesMathematics, 2023
The main results of the study of the convergence rate of quasi-Newton minimization methods were obtained under the assumption that the method operates in the region of the extremum of the function, where there is a stable quadratic representation of the ...
Vladimir Krutikov   +3 more
doaj   +1 more source

Accelerating Symmetric Rank-1 Quasi-Newton Method with Nesterov’s Gradient for Training Neural Networks

open access: yesAlgorithms, 2021
Gradient-based methods are popularly used in training neural networks and can be broadly categorized into first and second order methods. Second order methods have shown to have better convergence compared to first order methods, especially in solving ...
S. Indrapriyadarsini   +4 more
doaj   +1 more source

Hybrid Newton-type method for a class of semismooth equations [PDF]

open access: yes, 2002
In this paper, we present a hybrid method for the solution of a class of composite semismooth equations encountered frequently in applications. The method is obtained by combining a generalized finite-difference Newton method to an inexpensive direct ...
Pieraccini, Sandra
core   +1 more source

Self-decisive algorithm for unconstrained optimization problems as in biomedical image analysis

open access: yesFrontiers in Computational Neuroscience, 2022
This study describes the construction of a new algorithm where image processing along with the two-step quasi-Newton methods is used in biomedical image analysis.
Farah Jaffar   +4 more
doaj   +1 more source

Asynchronous parallel stochastic Quasi-Newton methods [PDF]

open access: yesParallel Computing, 2021
Although first-order stochastic algorithms, such as stochastic gradient descent, have been the main force to scale up machine learning models, such as deep neural nets, the second-order quasi-Newton methods start to draw attention due to their effectiveness in dealing with ill-conditioned optimization problems.
Qianqian Tong   +4 more
openaire   +3 more sources

Enhancing Quasi-Newton Acceleration for Fluid-Structure Interaction

open access: yesMathematical and Computational Applications, 2022
We propose two enhancements of quasi-Newton methods used to accelerate coupling iterations for partitioned fluid-structure interaction. Quasi-Newton methods have been established as flexible, yet robust, efficient and accurate coupling methods of multi ...
Kyle Davis   +2 more
doaj   +1 more source

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