A symmetric rank-one quasi-Newton line-search method using negative curvature directions

DOI10.1080/10556788.2010.544311zbMath1225.90130OpenAlexW1979563549MaRDI QIDQ3093055

Figen Oztoprak, Ş. İlker Birbil

Publication date: 12 October 2011

Published in: Optimization Methods and Software (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/10556788.2010.544311

zbMATH Keywords

negative curvaturequasi-NewtonSR1 updateunconstrained

Mathematics Subject Classification ID

Nonlinear programming (90C30) Methods of quasi-Newton type (90C53)

Related Items (2)

Limited memory methods with improved symmetric rank-one updates and its applications on nonlinear image restoration ⋮ A symmetric rank-one quasi-Newton method for nonnegative matrix factorization

Uses Software

• CUTEr
• KELLEY
• Algorithm 738

Cites Work

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• Convergence of quasi-Newton matrices generated by the symmetric rank one update
• Local convergence of the symmetric rank-one iteration
• Nonmonotone curvilinear line search methods for unconstrained optimization
• Nonconvex optimization using negative curvature within a modified linesearch
• A modular system of algorithms for unconstrained minimization
• LAPACK Users' Guide
• Quasi-Newton Methods, Motivation and Theory
• Algorithm 738: a software package for unconstrained optimization using tensor methods
• Eigenvalues and switching algorithms for Quasi-Newton updates
• Exploiting negative curvature directions in linesearch methods for unconstrained optimization
• A Theoretical and Experimental Study of the Symmetric Rank-One Update
• Analysis of a Symmetric Rank-One Trust Region Method
• A modified rank one update which converges \(Q\)-superlinearly
• Benchmarking optimization software with performance profiles.

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