A truncated Newton method with nonmonotone line search for unconstrained optimization
Journal of Optimization Theory and Applications
TNPACK—A truncated Newton minimization package for large-scale problems: I. Algorithm and usage
ACM Transactions on Mathematical Software (TOMS)
Nonmonotonic trust region algorithm
Journal of Optimization Theory and Applications
CUTE: constrained and unconstrained testing environment
ACM Transactions on Mathematical Software (TOMS)
Nonmonotone curvilinear line search methods for unconstrained optimization
Computational Optimization and Applications
An assessment of nonmonotone linesearch techniques for unconstrained optimization
SIAM Journal on Scientific Computing
The symmetric eigenvalue problem
The symmetric eigenvalue problem
Lancelot: A FORTRAN Package for Large-Scale Nonlinear Optimization (Release A)
Lancelot: A FORTRAN Package for Large-Scale Nonlinear Optimization (Release A)
Lanczos Algorithms for Large Symmetric Eigenvalue Computations, Vol. 1
Lanczos Algorithms for Large Symmetric Eigenvalue Computations, Vol. 1
Iterative computation of negative curvature directions in large scale optimization
Computational Optimization and Applications
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Recently, in [12] a very general class oftruncated Newton methods has been proposed for solving large scale unconstrained optimization problems. In this work we present the results of an extensive numericalexperience obtained by different algorithms which belong to the preceding class. This numerical study, besides investigating which arethe best algorithmic choices of the proposed approach, clarifies some significant points which underlies every truncated Newton based algorithm.