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Publication:3203937
zbMath0716.65055MaRDI QIDQ3203937
Publication date: 1990
Full work available at URL: https://eudml.org/doc/27752
Title: zbMATH Open Web Interface contents unavailable due to conflicting licenses.
unconstrained minimizationtest problemsvariable metric algorithmsBFGS-methodscontrolled scalingrank-one method
Related Items (10)
Computational experience with known variable metric updates ⋮ Family of optimally conditioned quasi-Newton updates for unconstrained optimization ⋮ Global convergence and the Powell singular function ⋮ Limited memory methods with improved symmetric rank-one updates and its applications on nonlinear image restoration ⋮ Unnamed Item ⋮ Unnamed Item ⋮ Variable metric methods for unconstrained optimization and nonlinear least squares ⋮ Variationally derived scaling and variable metric updates from the preconvex part of the Broyden family ⋮ Generalized Polak-Ribière algorithm ⋮ Sizing the BFGS and DFP updates: Numerical study
Uses Software
Cites Work
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- Quasi-Newton-Verfahren vom Rang-Eins-Typ zur Lösung unrestringierter Minimierungsprobleme. II: n-Schritt-quadratische Konvergenz für Restart-Varianten
- Conditions for variable-metric algorithms to be conjugate-gradient algorithms
- Local convergence analysis for partitioned quasi-Newton updates
- Variable metric algorithms: Necessary and sufficient conditions for identical behaviour of nonquadratic functions
- A class of rank-one positive definite qnasi-newton updates for unconstrained minimization2
- Least-Change Updates to Cholesky Factors Subject to the Nonlinear Quasi-Newton Condition
- Testing a Class of Methods for Solving Minimization Problems with Simple Bounds on the Variables
- Global Convergence of a Cass of Quasi-Newton Methods on Convex Problems
- Quasi-Newton Algorithms with Updates from the Preconvex Part of Broyden's Family
- Testing Unconstrained Optimization Software
- Self-Scaling Variable Metric (SSVM) Algorithms
- Methods for Computing and Modifying the LDV Factors of a Matrix
- Optimal conditioning of self-scaling variable Metric algorithms
- On the convergence rate of imperfect minimization algorithms in Broyden'sβ-class
- Matrix conditioning and nonlinear optimization
- A Family of Variable-Metric Methods Derived by Variational Means
- A new approach to variable metric algorithms
- The Convergence of a Class of Double-rank Minimization Algorithms 1. General Considerations
- Conditioning of Quasi-Newton Methods for Function Minimization
- Minimization Algorithms Making Use of Non-quadratic Properties of the Objective Function
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