Conjugate direction methods with variable storage

DOI10.1007/BF01583797zbMath0482.90078MaRDI QIDQ3941206

Nocedal, Jorge, Larry Nazareth

Publication date: 1982

Published in: Mathematical Programming (Search for Journal in Brave)

zbMATH Keywords

large optimization problemsconjugate gradient algorithmsquasi-Newton matricesvariable storagefinite termination properties

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Nonlinear programming (90C30) Quadratic programming (90C20)

Related Items (5)

A nonlinearly preconditioned conjugate gradient algorithm for rank‐R canonical tensor approximation ⋮ Inertia-preserving secant updates ⋮ Updating Quasi-Newton Matrices with Limited Storage ⋮ On diagonally-preconditioning the 2-step BFGS method with accumulated steps for linearly constrained nonlinear programming ⋮ On diagonally preconditioning the truncated Newton method for super-scale linearly constrained nonlinear prrogramming

Uses Software

• L-BFGS

Cites Work

• Unnamed Item
• A conjugate direction algorithm without line searches
• A Relationship between the BFGS and Conjugate Gradient Algorithms and Its Implications for New Algorithms
• Updating Quasi-Newton Matrices with Limited Storage
• Conjugate Gradient Algorithms: Quadratic Termination without Linear Searches
• Quasi-Newton Methods, Motivation and Theory
• A combined conjugate-gradient quasi-Newton minimization algorithm
• Extending the relationship between the conjugate gradient and BFGS algorithms
• Restart procedures for the conjugate gradient method
• Conjugate Gradient Methods with Inexact Searches
• Function minimization by conjugate gradients
• The Convergence of a Class of Double-rank Minimization Algorithms 1. General Considerations
• Methods of conjugate gradients for solving linear systems

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