A framework of conjugate direction methods for symmetric linear systems in optimization
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Other versions of this item:
- Giovanni Fasano, 2014. "A Framework of Conjugate Direction Methods for Symmetric Linear Systems in Optimization," Papers 1408.6043, arXiv.org.
References listed on IDEAS
- Giovanni Fasano & Massimo Roma, 2013. "Preconditioning Newton–Krylov methods in nonconvex large scale optimization," Computational Optimization and Applications, Springer, vol. 56(2), pages 253-290, October.
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KeywordsKrylov-based Methods; Conjugate Direction Methods; Conjugacy Loss and Error Analysis; Preconditioning.;
- C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
- C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
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