Nonmonotone spectral gradient method based on memoryless symmetric rank-one update for large-scale unconstrained optimization

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Nonmonotone spectral gradient method based on memoryless symmetric rank-one update for large-scale unconstrained optimization

This paper proposes a nonmonotone spectral gradient method for solving large-scale unconstrained optimization problems. The spectral parameter is derived from the eigenvalues of an optimally sized memoryless symmetric rank-one matrix obtained under the measure defined as a ratio of the determinant...

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Bibliographic Details
Main Authors:	Hong, Seng Sim, Chuei, Yee Chen, Wah, June Leong, Jiao, Li
Format:	Article
Published:	American Institute of Mathematical Sciences 2021
Online Access:	http://psasir.upm.edu.my/id/eprint/94373/

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