In this paper a new class of quasi-Newton methods, named LQN, is introduced in order to solve unconstrained minimization problems. The novel approach, which generalizes classical BFGS methods, is based on a Hessian updating formula involving an algebra L of matrices simultaneously diagonalized by a fast unitary transform. The complexity per step of LQN methods is O(n log_2 n), thereby improving considerably BFGS computational efficiency. Moreover, since LQN's iterative scheme utilizes single-indexed arrays, only O(n) memory allocations are required. Global convergence properties are investigated. In particular a global convergence result is obtained under suitable assumptions on f. Numerical experiences [7] confirm that LQN methods are particularly recommended for large scale problems.
Di Fiore, C., Fanelli, S., Lepore, F., & Zellini, P. (2003). Matrix algebras in Quasi-Newton methods for unconstrained minimization. NUMERISCHE MATHEMATIK, 94, 479-500.
Tipologia: | Articolo su rivista |
Citazione: | Di Fiore, C., Fanelli, S., Lepore, F., & Zellini, P. (2003). Matrix algebras in Quasi-Newton methods for unconstrained minimization. NUMERISCHE MATHEMATIK, 94, 479-500. |
IF: | Con Impact Factor ISI |
Lingua: | English |
Settore Scientifico Disciplinare: | Settore MAT/08 - Analisi Numerica |
Revisione (peer review): | Sì, ma tipo non specificato |
Tipo: | Articolo |
Rilevanza: | Rilevanza internazionale |
Digital Object Identifier (DOI): | http://dx.doi.org/10.1007/s00211-002-0410-4 |
Stato di pubblicazione: | Pubblicato |
Data di pubblicazione: | 2003 |
Titolo: | Matrix algebras in Quasi-Newton methods for unconstrained minimization |
Autori: | |
Autori: | Di Fiore, C; Fanelli, S; Lepore, F; Zellini, P |
Appare nelle tipologie: | 01 - Articolo su rivista |