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arXiv · 1510.06378

On solving large-scale limited-memory quasi-Newton equations

Jennifer B. Erway·Roummel F. Marcia
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Abstract

We consider the problem of solving linear systems of equations arising with limited-memory members of the restricted Broyden class of updates and the symmetric rank-one (SR1) update. In this paper, we propose a new approach based on a practical implementation of the compact representation for the inverse of these limited-memory matrices. Numerical results suggest that the proposed method compares favorably in speed and accuracy to other algorithms and is competitive with several update-specific methods available to only a few members of the Broyden class of updates. Using the proposed approach has an additional benefit: The condition number of the system matrix can be computed efficiently.

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Jennifer B. Erway, Roummel F. Marcia. 2015-10-21. On solving large-scale limited-memory quasi-Newton equations. https://arxiv.org/abs/1510.06378

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