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Extension for Large-Scale Problems
"... Scriptie ingediend met het oog op het behalen van de graad van Licentiaat in de ..."
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Scriptie ingediend met het oog op het behalen van de graad van Licentiaat in de
Tikhonov Regularization for Large Scale Problems
, 1997
"... Tikhonov regularization is a powerful tool for the solution of ill-posed linear systems and linear least squares problems. The choice of the regularization parameter is a crucial step, and many methods have been proposed for this purpose. However, efficient and reliable methods for large scale pro ..."
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Cited by 31 (1 self)
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Tikhonov regularization is a powerful tool for the solution of ill-posed linear systems and linear least squares problems. The choice of the regularization parameter is a crucial step, and many methods have been proposed for this purpose. However, efficient and reliable methods for large scale
PARAFAC ALGORITHMS FOR LARGE-SCALE PROBLEMS
"... Parallel factor analysis (PARAFAC, called also CP model)) is a tensor (multiway array) factorization method which allows to find hidden factors (component matrices) from a multidimensional data. Most of the existing algorithms for the PARAFAC, especially the alternating least squares (ALS) algorithm ..."
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Cited by 7 (3 self)
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) algorithm need to compute Khatri-Rao products of tall factors and multiplication of large-scale matrices and due to this require high computational cost and large memory and are not suitable for very large-scale problems. Hence, PARAFAC for large-scale data tensors is still a challenging problem
Parallel Iterative Methods for Nonsymmetric Large-Scale Problems
, 1995
"... This report summarizes our work on parallel iterative algorithms for large-scale problems. The work focuses on methods for nonsymmetric matrices, which are generally considered more difficult to treat than symmetric matrices. Thus, the work continues and generalizes the results already presented in ..."
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Cited by 2 (0 self)
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This report summarizes our work on parallel iterative algorithms for large-scale problems. The work focuses on methods for nonsymmetric matrices, which are generally considered more difficult to treat than symmetric matrices. Thus, the work continues and generalizes the results already presented
Generalized Cross-Validation for Large Scale Problems
- J. Comput. Graph. Stat
, 1995
"... . Although generalized cross-validation is a popular tool for calculating a regularization parameter it has been rarely applied to large scale problems until recently. A major difficulty lies in the evaluation of the cross-validation function which requires the calculation of the trace of an inverse ..."
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Cited by 20 (6 self)
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. Although generalized cross-validation is a popular tool for calculating a regularization parameter it has been rarely applied to large scale problems until recently. A major difficulty lies in the evaluation of the cross-validation function which requires the calculation of the trace
2008), On the location and continuation of Hopf bifurcations in large-scale problems
"... 2007 CL_MATCONT is a MATLAB package for the study of dynamical systems and their bifurcations. It uses a minimally augmented system for continuation of the Hopf curve. The Continuation of Invariant Subspaces (CIS) algorithm produces a smooth orthonormal basis for an invariant subspace R(s) of a para ..."
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Cited by 2 (1 self)
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parameter-dependent matrix A(s). We extend a mini-mally augmented system technique for location and continuation of Hopf bifurcations to large-scale problems using the CIS algorithm, which has been incorporated into CL_MATCONT. We compare this approach with using a standard augmented system and show that a
Computational schemes for large-scale problems in extended linearquadratic programming
- Mathematical Programming
, 1990
"... Abstract. Numerical approaches are developed for solving large-scale problems of extended linear-quadratic programming that exhibit Lagrangian separability in both primal and dual variables simultaneously. Such problems are kin to large-scale linear complementarity models as derived from application ..."
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Cited by 11 (1 self)
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Abstract. Numerical approaches are developed for solving large-scale problems of extended linear-quadratic programming that exhibit Lagrangian separability in both primal and dual variables simultaneously. Such problems are kin to large-scale linear complementarity models as derived from
Regularization Tools for Training Feed-Forward Neural Networks Part II: Large-scale problems
, 1996
"... this paper, we propose optimization methods explicitly applied to the nonlinear regularized problem for large-scale problems. To be specific, we formulate ..."
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Cited by 4 (3 self)
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this paper, we propose optimization methods explicitly applied to the nonlinear regularized problem for large-scale problems. To be specific, we formulate
Computational Issues in Damping Identification for Large Scale Problems
- Proceedings 1997 ASME Design Technical Conference, paper No. DETC97/VIB-3835
, 1997
"... Damage detection and diagnostic techniques using vibration responses that depend on analytical models provide more information about a structure’s integrity than those that are not model based. The drawback of these approaches is that some form of workable model is required. Typically, models of pra ..."
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Cited by 2 (1 self)
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in the damping matrices and the health of a structure. The objective of this research is to investigate the numerical problems associated with computing damping matrices using inverse methods. Two damping identification methods are tested for efficiency in large-scale applications. One is an iterative routine
Computational Issues in Damping Identification for Large Scale Problems
- Proceedings 1997 ASME Design Technical Conference, paper No. DETC97/VIB-3835
, 1997
"... Damage detection and diagnostic techniques using vibration responses that depend on analytical models provide more information about a structure's integrity than those that are not model based. The drawback of these approaches is that some form of workable model is required. Typically, models ..."
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change in the damping matrices and the health of a structure. The objective of this research is to investigate the numerical problems associated with computing damping matrices using inverse methods. Two damping identification methods are tested for e#ciency in large-scale applications. One
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