New limited memory bundle method for large-scale nonsmooth optimization
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Publication:5460656
DOI10.1080/10556780410001689225zbMath1068.90101OpenAlexW1963488456WikidataQ109315022 ScholiaQ109315022MaRDI QIDQ5460656
M. Haarala, Marko M. Mäkelä, Kaisa M. Miettinen
Publication date: 18 July 2005
Published in: Optimization Methods and Software (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/10556780410001689225
large-scale optimizationvariable metric methodstest problemsbundle methodsnondifferentiable programminglimited memory methods
Nonlinear programming (90C30) Derivative-free methods and methods using generalized derivatives (90C56)
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Uses Software
Cites Work
- Unnamed Item
- On the limited memory BFGS method for large scale optimization
- Partitioned variable metric updates for large structured optimization problems
- Representations of quasi-Newton matrices and their use in limited memory methods
- Globally convergent variable metric method for convex nonsmooth unconstrained minimization
- Comparison of formulations and solution methods for image restoration problems
- An Ellipsoid Trust Region Bundle Method for Nonsmooth Convex Minimization
- An Efficient Method to Solve the Minimax Problem Directly
- BFGS with Update Skipping and Varying Memory
- Survey of Bundle Methods for Nonsmooth Optimization
- Gobally convergent variable metric method for nonconvex nondifferentiable unconstrained minimization
- Benchmarking optimization software with performance profiles.
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