A Newton-like trust region method for large-scale unconstrained nonconvex minimization

DOI10.1155/2013/478407zbMath1291.90192OpenAlexW2032089608WikidataQ58916376 ScholiaQ58916376MaRDI QIDQ2015579

Zhang Chenhui, Yang Weiwei, Cao Mingyuan, Yang Yueting

Publication date: 23 June 2014

Published in: Abstract and Applied Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2013/478407

Mathematics Subject Classification ID

Large-scale problems in mathematical programming (90C06) Nonconvex programming, global optimization (90C26) Methods of quasi-Newton type (90C53)

Related Items

A self-adaptive trust region method for extreme \(\mathcal {B}\)-eigenvalues of symmetric tensors ⋮ Faster Riemannian Newton-type optimization by subsampling and cubic regularization

Uses Software

• GALAHAD
• SNOPT
• L-BFGS
• minpack

Cites Work

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