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Adaptive matrix algebras in unconstrained minimization.
- Source :
-
Linear Algebra & its Applications . Apr2015, Vol. 471, p544-568. 25p. - Publication Year :
- 2015
-
Abstract
- In this paper we study adaptive L ( k ) QN methods, involving special matrix algebras of low complexity, to solve general (non-structured) unconstrained minimization problems. These methods, which generalize the classical BFGS method, are based on an iterative formula which exploits, at each step, an ad hoc chosen matrix algebra L ( k ) . A global convergence result is obtained under suitable assumptions on f . [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 00243795
- Volume :
- 471
- Database :
- Academic Search Index
- Journal :
- Linear Algebra & its Applications
- Publication Type :
- Academic Journal
- Accession number :
- 101139586
- Full Text :
- https://doi.org/10.1016/j.laa.2015.01.010