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Global convergence properties of conjugate gradient methods for optimization

Abstract : We study the convergence of nonlinear conjugate gradient methods without restarts and with practical line searches. The analysis covers two classes of methods that are globally convergent on smooth, non convex functions. Some properties of the Fletcher-Reeves method play an important role in the first family, whereas the second family shares an important property with the Polak-Ribiere method. Numerical experiments are presented.
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https://hal.inria.fr/inria-00075291
Contributor : Rapport de Recherche Inria <>
Submitted on : Wednesday, May 24, 2006 - 5:53:12 PM
Last modification on : Thursday, February 11, 2021 - 2:50:07 PM
Long-term archiving on: : Tuesday, April 12, 2011 - 10:21:48 PM

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  • HAL Id : inria-00075291, version 1

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Jean Charles Gilbert, J. Nocedal. Global convergence properties of conjugate gradient methods for optimization. RR-1268, INRIA. 1990. ⟨inria-00075291⟩

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