Zobrazeno 1 - 10
of 4 627
pro vyhledávání: '"unconstrained optimization"'
Publikováno v:
AIMS Mathematics, Vol 9, Iss 10, Pp 27272-27292 (2024)
We investigated the challenge of unconstrained distributed optimization with a time-varying objective function, employing a prediction-correction approach. Our method introduced a backward Euler prediction step that used the differential information
Externí odkaz:
https://doaj.org/article/f52b39bcf48848b48aaa4e2acdd79a18
Autor:
Viktor Zadachyn
Publikováno v:
Кібернетика та комп'ютерні технології, Iss 3, Pp 12-24 (2024)
Introduction. Methods of unconstrained optimization play a significant role in machine learning [1–6]. When solving practical problems in machine learning, such as tuning nonlinear regression models, the extremum point of the chosen optimality crit
Externí odkaz:
https://doaj.org/article/cb875fd0d5b447d9aa86da991d217ee6
Autor:
H. Sharma, R.K. Nayak
Publikováno v:
Iranian Journal of Numerical Analysis and Optimization, Vol 14, Iss Issue 3, Pp 970-990 (2024)
The Barzilai–Borwein method offers efficient step sizes for large-scale un-constrained optimization problems. However, it may not guarantee global convergence for nonquadratic objective functions. Simulated annealing-based on Barzilai–Borwein (SA
Externí odkaz:
https://doaj.org/article/7757ebb83555440ab7cbed5773da6fe3
Autor:
Yulin Cheng, Jing Gao
Publikováno v:
AIMS Mathematics, Vol 9, Iss 9, Pp 25232-25252 (2024)
In this paper, an augmented memoryless BFGS quasi-Newton method was proposed for solving unconstrained optimization problems. Based on a new modified secant equation, an augmented memoryless BFGS update formula and an efficient optimization algorithm
Externí odkaz:
https://doaj.org/article/89889ce2aeda4af7b808d7e76537fbc8
Publikováno v:
Engineering Computations, 2024, Vol. 41, Issue 5, pp. 1203-1232.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/EC-12-2023-0912
Autor:
Seyed Hamzeh Mirzaei, Ali Ashrafi
Publikováno v:
Journal of Inequalities and Applications, Vol 2024, Iss 1, Pp 1-22 (2024)
Abstract In this paper, a new appropriate diagonal matrix estimation of the Hessian is introduced by minimizing the Byrd and Nocedal function subject to the weak secant equation. The Hessian estimate is used to correct the framework of a nonmonotone
Externí odkaz:
https://doaj.org/article/156d327cf1de4f13a99cacd0b9966394
Autor:
Abd Hassan, Hamsa Saeed
Publikováno v:
مجلة التربية والعلم, Vol 33, Iss 2, Pp 123-133 (2024)
Conjugate gradient algorithms come in a wide range of flavors. The conjugate gradient technique primarily concentrates on the spectral parameter. It follows the standard method proposed by Hastens and Stiefel, In this study, we have devised an innova
Externí odkaz:
https://doaj.org/article/1751391ddd2f4ada9b04fe490860b8a5
Autor:
Farah F. Ghazi, Luma N. M. Tawfiq
Publikováno v:
An International Journal of Optimization and Control: Theories & Applications, Vol 14, Iss 3 (2024)
In this article, we design an optimal neural network based on new LM training algorithm. The traditional algorithm of LM required high memory, storage and computational overhead because of it required the updated of Hessian approximations in each ite
Externí odkaz:
https://doaj.org/article/720ae39c7761418b8da496dfc8abd9df