Properties and Application of Incomplete Orthogonalization in the Directions of Gradient Difference in Optimization Methods

This paper considers the problem of unconstrained minimization of smooth functions. Despite the high efficiency of quasi-Newton methods such as BFGS, their performance degrades in ill-conditioned problems with unstable or rapidly varying Hessians—for example, in functions with curved ravine structur...

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Bibliografische gegevens

Hoofdauteurs:	Vladimir Krutikov, Elena Tovbis, Svetlana Gutova, Ivan Rozhnov, Lev Kazakovtsev
Formaat:	Artigo
Taal:	Inglês
Gepubliceerd in:	MDPI AG 2025-12-01
Reeks:	Mathematics
Onderwerpen:	minimization method relaxation subgradient method iterative least squares convergence rate
Online toegang:	https://www.mdpi.com/2227-7390/13/24/4036
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