Block BFGS Methods

DOI10.1137/16M1092106zbMath1397.90402arXiv1609.00318OpenAlexW2963242954MaRDI QIDQ4641646

Wenbo Gao, Donald Goldfarb

Publication date: 18 May 2018

Published in: SIAM Journal on Optimization (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1609.00318

zbMATH Keywords

unconstrained optimizationquasi-Newton methodsBFGSblock updates

Mathematics Subject Classification ID

Nonconvex programming, global optimization (90C26) Methods of quasi-Newton type (90C53)

Related Items (3)

Quasi-Newton methods for machine learning: forget the past, just sample ⋮ An overview of stochastic quasi-Newton methods for large-scale machine learning ⋮ Quasi-Newton methods: superlinear convergence without line searches for self-concordant functions

Uses Software

• L-BFGS
• LIBSVM
• ve08
• NETLIB LP Test Set
• minFunc
• ADiGator

Cites Work

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• A Stochastic Quasi-Newton Method for Large-Scale Optimization
• On the limited memory BFGS method for large scale optimization
• Local convergence analysis for partitioned quasi-Newton updates
• On the Global Convergence of the BFGS Method for Nonconvex Unconstrained Optimization Problems
• Global Convergence of a Cass of Quasi-Newton Methods on Convex Problems
• Algorithms for nonlinear constraints that use lagrangian functions
• A repository of convex quadratic programming problems
• Algorithm 984
• A Characterization of Superlinear Convergence and Its Application to Quasi-Newton Methods
• A Family of Variable-Metric Methods Derived by Variational Means
• A modified BFGS method and its global convergence in nonconvex minimization
• Benchmarking optimization software with performance profiles.

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