In this paper, we propose a regularized factorized quasi-Newton method with a new Armijo-type line search and prove its global convergence for nonlinear least squares problems. This convergence result is extended to the regularized BFGS and DFP methods for solving strictly convex minimization problems. Some numerical results are presented to show efficiency of the proposed method. Mathematical subject classification: 90C53, 65K05
In this paper, we provide theoretical analysis for a cubic regularization of Newton method as applie...
A class of algorithms for nonlinearly constrained optimization problems is proposed. The subproblems...
In this thesis we study the local convergence of quasi-Newton methods for nonlinear optimization pro...
Abstract We are concerned with nonlinear least squares problems. It is known that structured quasi-N...
In this paper, by using a modified BFGS (MBFGS) update, we propose a structured MBFGS update for the...
This work addresses a spectral correction for the Gauss-Newton model in the solution of nonlinear le...
Abstract This paper is concerned with local and q-superlinear convergence of structured quasi-Newton...
An optimization problem that does not have an unique local minimum is often very difficult to solve....
In this paper, we present a brief survey of methods for solving nonlinear least-squares problems. We...
The convergence properties of the new Regularized Euclidean Residual method for solving general nonl...
Abstract In this paper, non-monotone line search procedure is studied, which is combined with the no...
This paper studies convergence properties of regularized Newton methods for minimizing a convex func...
Recently, we have presented a projected structured algorithm for solving constrained nonlinear least...
In this paper we present a Quasi-Newton type method, which applies to large and sparse nonlinear sys...
Abstract. This paper studies convergence properties of regularized Newton methods for minimizing a c...
In this paper, we provide theoretical analysis for a cubic regularization of Newton method as applie...
A class of algorithms for nonlinearly constrained optimization problems is proposed. The subproblems...
In this thesis we study the local convergence of quasi-Newton methods for nonlinear optimization pro...
Abstract We are concerned with nonlinear least squares problems. It is known that structured quasi-N...
In this paper, by using a modified BFGS (MBFGS) update, we propose a structured MBFGS update for the...
This work addresses a spectral correction for the Gauss-Newton model in the solution of nonlinear le...
Abstract This paper is concerned with local and q-superlinear convergence of structured quasi-Newton...
An optimization problem that does not have an unique local minimum is often very difficult to solve....
In this paper, we present a brief survey of methods for solving nonlinear least-squares problems. We...
The convergence properties of the new Regularized Euclidean Residual method for solving general nonl...
Abstract In this paper, non-monotone line search procedure is studied, which is combined with the no...
This paper studies convergence properties of regularized Newton methods for minimizing a convex func...
Recently, we have presented a projected structured algorithm for solving constrained nonlinear least...
In this paper we present a Quasi-Newton type method, which applies to large and sparse nonlinear sys...
Abstract. This paper studies convergence properties of regularized Newton methods for minimizing a c...
In this paper, we provide theoretical analysis for a cubic regularization of Newton method as applie...
A class of algorithms for nonlinearly constrained optimization problems is proposed. The subproblems...
In this thesis we study the local convergence of quasi-Newton methods for nonlinear optimization pro...