Hongtruong Pham
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View article: A Diagonal BFGS Update Algorithm with Inertia Acceleration Technology for Minimizations
A Diagonal BFGS Update Algorithm with Inertia Acceleration Technology for Minimizations Open
We integrate the diagonal quasi-Newton update approach with the enhanced BFGS formula proposed by Wei, Z., Yu, G., Yuan, G., Lian, Z. \cite{b1}, incorporating extrapolation techniques and inertia acceleration technology. This method, desig…
View article: A Stochastic Recursive Gradient Algorithm with Inertial Extrapolation for Non-convex Problems and machine learning
A Stochastic Recursive Gradient Algorithm with Inertial Extrapolation for Non-convex Problems and machine learning Open
In recent years, extrapolation acceleration technology has been widely employed across various algorithms; however, its application in machine learning has yielded limited achievements. Therefore, building upon the foundation of inertial a…
View article: Globally convergent conjugate gradient algorithms without the Lipschitz condition for nonconvex optimization
Globally convergent conjugate gradient algorithms without the Lipschitz condition for nonconvex optimization Open
It is well known that under the Wolfe–Powell inexact line search, the global convergence of the nonlinear conjugate gradient method always requires the Lipschitz continuous condition for nonconvex functions. In this paper, we find that the…
View article: A Modified Dai–Liao Conjugate Gradient Method with a New Parameter for Solving Image Restoration Problems
A Modified Dai–Liao Conjugate Gradient Method with a New Parameter for Solving Image Restoration Problems Open
One adaptive choice for the parameter of the Dai–Liao conjugate gradient method is suggested in this paper, which is obtained with modified quasi–Newton equation. So we get a modified Dai–Liao conjugate gradient method. Some interesting fe…
View article: A Modified Three-Term Type CD Conjugate Gradient Algorithm for Unconstrained Optimization Problems
A Modified Three-Term Type CD Conjugate Gradient Algorithm for Unconstrained Optimization Problems Open
Conjugate gradient methods are well-known methods which are widely applied in many practical fields. CD conjugate gradient method is one of the classical types. In this paper, a modified three-term type CD conjugate gradient algorithm is p…
View article: Global Convergence of a Modified Two-Parameter Scaled BFGS Method with Yuan-Wei-Lu Line Search for Unconstrained Optimization
Global Convergence of a Modified Two-Parameter Scaled BFGS Method with Yuan-Wei-Lu Line Search for Unconstrained Optimization Open
The BFGS method is one of the most efficient quasi-Newton methods for solving small- and medium-size unconstrained optimization problems. For the sake of exploring its more interesting properties, a modified two-parameter scaled BFGS metho…
View article: A Modified Three-Term Conjugate Gradient Algorithm for Large-Scale Nonsmooth Convex Optimization
A Modified Three-Term Conjugate Gradient Algorithm for Large-Scale Nonsmooth Convex Optimization Open
It is well known that Newton and quasi-Newton algorithms are effective to small and medium scale smooth problems because they take full use of corresponding gradient function’s information but fail to solve nonsmooth pr... | Find, read and…
View article: On a new algorithm for solving variational inequality and fixed point problems
On a new algorithm for solving variational inequality and fixed point problems Open
The paper is concerned with the problem of finding a common solution of a variational inequality problem governed by Lipschitz continuous monotone mappings and a fixed point problem of nonexpansive mappings.To solve this problem, we introd…
View article: A Conjugate Gradient Algorithm under Yuan-Wei-Lu Line Search Technique for Large-Scale Minimization Optimization Models
A Conjugate Gradient Algorithm under Yuan-Wei-Lu Line Search Technique for Large-Scale Minimization Optimization Models Open
This paper gives a modified Hestenes and Stiefel (HS) conjugate gradient algorithm under the Yuan-Wei-Lu inexact line search technique for large-scale unconstrained optimization problems, where the proposed algorithm has the following prop…