Updating Quasi-Newton Matrices With Limited Storage
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Summary
An update formula which generates matrices using information from the last m iterations, where m is any number supplied by the user, and the BFGS method is considered to be the most efficient.
- Type
- article
- Published
- 1980-09-01
- Cited by
- 2,968
- References
- 16
- Access
- Open access
- OpenAlex
- https://openalex.org/W2051669046
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:9033333
Keywords
Mathematics, Matrix (chemical analysis), Broyden–Fletcher–Goldfarb–Shanno algorithm, Minification, Algorithm
References
- Relationship between the BFGS and conjugate gradient algorithms
- A Study of Conjugate Gradient Methods.
- The solution of nonlinear finite element equations
- On sparse and symmetric matrix updating subject to a linear equation
- On the convergence rate of imperfect minimization algorithms in Broyden'sβ-class
- On variable-metric methods for sparse Hessians
- Quasi-Newton Methods, Motivation and Theory
- A combined conjugate-gradient quasi-Newton minimization algorithm
- A New Approach to Variable Metric Algorithms
- The Convergence of a Class of Double-rank Minimization Algorithms 1. General Considerations
- The convergence of a class of double-rank minimization algorithms
- On Sparse and Symmetric Matrix Updating Subject to a Linear Equation
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- Local Exchange Potentials in Density Functional Theory
- Density functional investigations on structural and electronic properties of anionic and neutral sodium clusters NaN (N = 40–147): comparison with the experimental photoelectron spectra
- Evolution of the potential energy landscape with static pulling force for two model proteins.
- Explicit all-atom modeling of realistically sized ligand-capped nanocrystals.
- Improved constrained optimization method for reaction-path determination in the generalized hybrid orbital quantum mechanical/molecular mechanical calculations.
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- Introducing mutations to modify the C13/C9 ratio in linoleic acid oxygenations catalyzed by rabbit 15-lipoxygenase: a QM/MM and MD study.
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- Material discovery by combining stochastic surface walking global optimization with a neural network
- Analysis of non-pharmaceutical interventions impacts on COVID-19 pandemic in Iran
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- Combining stationary ocean models and mean dynamic topography data = Kombination stationärer Ozeanmodelle mit Daten der mittleren dynamischen Topographie
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