Preconditioned nonlinear conjugate gradient methods based on a modified secant equation
This paper includes a twofold result for the Nonlinear Conjugate Gradient (NCG) method, in
large scale unconstrained optimization. First we consider a theoretical analysis, where …
large scale unconstrained optimization. First we consider a theoretical analysis, where …
Novel preconditioners based on quasi–Newton updates for nonlinear conjugate gradient methods
In this paper we study new preconditioners to be used within the nonlinear conjugate
gradient (NCG) method, for large scale unconstrained optimization. The rationale behind our …
gradient (NCG) method, for large scale unconstrained optimization. The rationale behind our …
An adaptive truncation criterion, for linesearch-based truncated Newton methods in large scale nonconvex optimization
Starting from the paper by Nash and Sofer (1990), we propose a heuristic adaptive
truncation criterion for the inner iterations within linesearch-based truncated Newton …
truncation criterion for the inner iterations within linesearch-based truncated Newton …
Updating constraint preconditioners for KKT systems in quadratic programming via low-rank corrections
This work focuses on the iterative solution of sequences of KKT linear systems arising in
interior point methods applied to large convex quadratic programming problems. This task is …
interior point methods applied to large convex quadratic programming problems. This task is …
[图书][B] Data-scalable Hessian preconditioning for distributed parameter PDE-constrained inverse problems
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Hessian preconditioners are the key to efficient numerical solution of large-scale distributed
parameter PDE-constrained inverse problems with highly informative data. Such inverse …
parameter PDE-constrained inverse problems with highly informative data. Such inverse …
Exploiting damped techniques for nonlinear conjugate gradient methods
In this paper we propose the use of damped techniques within Nonlinear Conjugate
Gradient (NCG) methods. Damped techniques were introduced by Powell and recently …
Gradient (NCG) methods. Damped techniques were introduced by Powell and recently …
Preconditioning strategies for nonlinear conjugate gradient methods, based on quasi-Newton updates
This paper reports two proposals of possible preconditioners for the Nonlinear Conjugate
Gradient (NCG) method, in large scale unconstrained optimization. On one hand, the …
Gradient (NCG) method, in large scale unconstrained optimization. On one hand, the …
[HTML][HTML] Data and performance profiles applying an adaptive truncation criterion, within linesearch-based truncated Newton methods, in large scale nonconvex …
In this paper, we report data and experiments related to the research article entitled “An
adaptive truncation criterion, for linesearch-based truncated Newton methods in large scale …
adaptive truncation criterion, for linesearch-based truncated Newton methods in large scale …
Dense conjugate initialization for deterministic PSO in applications: ORTHOinit+
This paper describes a class of novel initializations in Deterministic Particle Swarm
Optimization (DPSO) for approximately solving costly unconstrained global optimization …
Optimization (DPSO) for approximately solving costly unconstrained global optimization …
Quasi-newton based preconditioning and damped quasi-newton schemes for nonlinear conjugate gradient methods
In this paper, we deal with matrix-free preconditioners for nonlinear conjugate gradient
(NCG) methods. In particular, we review proposals based on quasi-Newton updates, and …
(NCG) methods. In particular, we review proposals based on quasi-Newton updates, and …