In this paper we study adaptive L(k)QNmethods, 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 hocchosen matrix algebra L(k). A global convergence result is obtained under suitable assumptions on f.
Cipolla, S., DI FIORE, C., Tudisco, F., Zellini, P. (2015). Adaptive matrix algebras in unconstrained minimization. LINEAR ALGEBRA AND ITS APPLICATIONS, 471, 544-568 [10.1016/j.laa.2015.01.010].
Adaptive matrix algebras in unconstrained minimization
DI FIORE, CARMINE;ZELLINI, PAOLO
2015-01-01
Abstract
In this paper we study adaptive L(k)QNmethods, 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 hocchosen matrix algebra L(k). A global convergence result is obtained under suitable assumptions on f.File in questo prodotto:
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