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What is Ha Am Iemak 2006 about?
This paper presents a globally convergent limited memory bundle method for large-scale nonsmooth optimization problems, focusing on locally Lipschitz continuous objective functions. The authors introduce modifications to a previously established algorithm, ensuring its effectiveness through numerical experiments that demonstrate its reliability for both convex and nonconvex problems. Key features include a limited memory approach to direction finding and a novel aggregation procedure for subgradients, which
- Author
- aleg
- Language
- EN