Search
Search Results
-
Practical gradient and conjugate gradient methods on flag manifolds
Flag manifolds, sets of nested sequences of linear subspaces with fixed dimensions, are rising in numerical analysis and statistics. The current...
-
Shape Optimization with Nonlinear Conjugate Gradient Methods
In this chapter, we investigate recently proposed nonlinear conjugate gradient (NCG) methods for shape optimization problems. We briefly introduce...
-
Conjugate Gradient Methods
These methods are characterized by very strong convergence properties and modest storage requirements. They are dedicated to solving large-scale...
-
Spectral conjugate gradient methods for vector optimization problems
In this work, we present an extension of the spectral conjugate gradient (SCG) methods for solving unconstrained vector optimization problems, with...
-
Quantum Polak Ribière Polyak Conjugate Gradient Method
The conjugate gradient methods deflect the steepest descent method by adding to it a positive multiple of the descent direction that uses in the...
-
Quantum Fletcher Reeves Conjugate Gradient Method
Numerous applications involve optimization problems, including image processing (Hassan Ibrahim et al. 2020), science (Lin et al. 2020a) and...
-
Two efficient three-term conjugate gradient methods for impulse noise removal from medical images
In this paper, we discuss two efficient three-term conjugate gradient methods ( ECG ) for impulse noise removal. The directions of ECG are first the...
-
Conjugate Direction Methods
We consider conjugate direction methods, Conjugate direction method a class of algorithms originally introduced as iterative methods for solving...
-
A class of spectral conjugate gradient methods for Riemannian optimization
Spectral conjugate gradient (SCG) methods are combinations of spectral gradient method and conjugate gradient (CG) methods, which have been well...
-
Quantum Variant of Dai Yuan Conjugate Gradient Method
This is well-known that Fletcher and Powell (1963) and Dai and Yuan (1999) conjugate gradient methods have good convergence properties. Al-Baali...
-
Multiobjective Conjugate Gradient Methods on Riemannian Manifolds
In this paper, we present the multiobjective optimization methods of conjugate gradient on Riemannian manifolds. The concepts of optimality and Wolfe...
-
Some improved Dai–Yuan conjugate gradient methods for large-scale unconstrained optimization problems
In this paper, we introduce some modifications of the classic conjugate gradient method Dai–Yuan, to solve large-scale unconstrained optimization...
-
Conjugate Gradient Method for finding Optimal Parameters in Linear Regression
Linear regression is one of the most celebrated approaches for modeling the relationship between independent and dependent variables in a prediction...
-
Optimal Scaling Parameters for Spectral Conjugate Gradient Methods
To improve upon numerical stability of the spectral conjugate gradient methods, two adaptive scaling parameters are introduced. One parameter is...
-
Nonlinear conjugate gradient for smooth convex functions
The method of nonlinear conjugate gradients (NCG) is widely used in practice for unconstrained optimization, but it satisfies weak complexity bounds...
-
Riemannian conjugate gradient methods for computing the extreme eigenvalues of symmetric tensors
In this paper, we propose two kinds of Riemannian conjugate gradient methods for computing the extreme eigenvalues of even order symmetric tensors....
-
Nonmonotone Quasi–Newton-based conjugate gradient methods with application to signal processing
Founded upon a sparse estimation of the Hessian obtained by a recent diagonal quasi-Newton update, a conjugacy condition is given, and then, a class...
-
Modified globally convergent Polak-Ribière-Polyak conjugate gradient methods with self-correcting property for large-scale unconstrained optimization
In this paper, we propose a modified Polak-Ribière-Polyak conjugate gradient method. Different from the existent methods, a dam** factor is...
-
Practical Restrictively Preconditioned Conjugate Gradient Methods for a Class of Block Two-by-Two Linear Systems
We further analyze the solution of a class of block two-by-two linear systems. Instead of using the preconditioned GMRES iteration methods, we...
-
Gravity interpretation using modified preconditioned conjugate gradient and reweighting of inversion methods: a case study from Iran
This study, a reweighting focusing (RF) inversion and modified preconditioned conjugate gradient (MPCG) inversion methods are described, and then,...
