An Improvement of the Pivoting Strategy in the Bunch and Kaufman Decomposition, Within Truncated Newton Methods
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Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-030-95380-5_5
Reference19 articles.
1. Bunch, J., Kaufman, L.: Some stable methods for calculating inertia and solving symmetric linear equations. Math. Comput. 31, 163–179 (1977)
2. Caliciotti, A., Fasano, G., Nash, S.G., Roma, M.: An adaptive truncation criterion, for linesearch-based truncated Newton methods in large scale nonconvex optimization. Oper. Res. Lett. 46, 7–12 (2018)
3. Caliciotti, A., Fasano, G., Nash, S.G., Roma, M.: Data and performance profiles applying an adaptive truncation criterion, within linesearch-based truncated Newton methods, in large scale nonconvex optimization. Data in Brief 17, 246–255 (2018)
4. Caliciotti, A., Fasano, G., Roma, M.: Preconditioned nonlinear conjugate gradient methods based on a modified secant equation. Appl. Math. Comput. 318, 196–214 (2018)
5. Caliciotti, A., Fasano, G., Potra, F., Roma, M.: Issues on the use of a modified Bunch and Kaufman decomposition for large scale Newton’s equation. Comput. Optim. Appl. 77, 627–651 (2020)
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