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Updating preconditioners for modified least squares problems

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Updating preconditioners for modified least squares problems

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Marín Mateos-Aparicio, J.; Mas Marí, J.; Guerrero-Flores, DJ.; Hayami, K. (2017). Updating preconditioners for modified least squares problems. Numerical Algorithms. 75(2):491-508. https://doi.org/10.1007/s11075-017-0315-z

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Título: Updating preconditioners for modified least squares problems
Autor: Marín Mateos-Aparicio, José Mas Marí, José Guerrero-Flores, Danny Joel Hayami, K.
Entidad UPV: Universitat Politècnica de València. Departamento de Matemática Aplicada - Departament de Matemàtica Aplicada
Fecha difusión:
Resumen:
[EN] In this paper, we analyze how to update incomplete Cholesky preconditioners to solve least squares problems using iterative methods when the set of linear relations is updated with some new information, a new variable ...[+]
Palabras clave: Least squares problems , Iterative methods , Preconditioners , Low-rank updates , Sparse matrices
Derechos de uso: Reserva de todos los derechos
Fuente:
Numerical Algorithms. (issn: 1017-1398 )
DOI: 10.1007/s11075-017-0315-z
Editorial:
Springer-Verlag
Versión del editor: http://doi.org/10.1007/s11075-017-0315-z
Código del Proyecto:
info:eu-repo/grantAgreement/MINECO//MTM2015-68805-REDT/ES/RED TEMATICA DE ALGEBRA LINEAL, ANALISIS MATRICIAL Y APLICACIONES/
info:eu-repo/grantAgreement/MINECO//MTM2014-58159-P/ES/PRECONDICIONADORES PARA SISTEMAS DE ECUACIONES LINEALES, PROBLEMAS DE MINIMOS CUADRADOS, CALCULO DE VALORES PROPIOS Y APLICACIONES TECNOLOGICAS/
Agradecimientos:
Partially supported by Spanish Grants MTM2014-58159-P and MTM2015-68805-REDT.
Tipo: Artículo

References

Alexander, S.T., Pan, C.T., Plemmons, R.J.: Analysis of a recursive least squares hyperbolic rotation algorithm for signal processing. Linear Algebra Appl. 98, 3–40 (1988)

Andrew, R., Dingle, N.: Implementing QR factorization updating algorithms on GPUs. Parallel Comput. 40(7), 161–172 (2014). doi: 10.1016/j.parco.2014.03.003 . http://www.sciencedirect.com/science/article/pii/S0167819114000337 . 7th Workshop on Parallel Matrix Algorithms and Applications

Benzi, M., T˚uma, M.: A robust incomplete factorization preconditioner for positive definite matrices. Numer. Linear Algebra Appl. 10(5-6), 385–400 (2003) [+]
Alexander, S.T., Pan, C.T., Plemmons, R.J.: Analysis of a recursive least squares hyperbolic rotation algorithm for signal processing. Linear Algebra Appl. 98, 3–40 (1988)

Andrew, R., Dingle, N.: Implementing QR factorization updating algorithms on GPUs. Parallel Comput. 40(7), 161–172 (2014). doi: 10.1016/j.parco.2014.03.003 . http://www.sciencedirect.com/science/article/pii/S0167819114000337 . 7th Workshop on Parallel Matrix Algorithms and Applications

Benzi, M., T˚uma, M.: A robust incomplete factorization preconditioner for positive definite matrices. Numer. Linear Algebra Appl. 10(5-6), 385–400 (2003)

Benzi, M., Szyld, D.B., Van Duin, A.: Orderings for incomplete factorization preconditioning of nonsymmetric problems. SIAM J. Sci. Comput. 20(5), 1652–1670 (1999)

Björck, Å.: Numerical methods for Least Squares Problems. SIAM, Philadelphia (1996)

Bru, R., Marín, J., Mas, J., T˚uma, M.: Preconditioned iterative methods for solving linear least squares problems. SIAM J. Sci. Comput. 36(4), A2002–A2022 (2014)

Cerdán, J., Marín, J., Mas, J.: Low-rank upyears of balanced incomplete factorization preconditioners. Numer. Algorithms. doi: 10.1007/s11075-016-0151-6 (2016)

Chambers, J.M.: Regression updating. J. Amer. Statist. Assoc. 66, 744–748 (1971)

Davis, T.A., Hu, Y.: The university of florida sparse matrix collection. ACM trans. Math. Software 38(1), 1–25 (2011)

Davis, T.A., Hager, W.W.: Modifying a sparse Cholesky factorization. SIAM J. Matrix Anal. Appl. 20, 606–627 (1999)

Davis, T.A., Hager, W.W.: Multiple-rank modifications of a sparse Cholesky factorization. SIAM J. Matrix Anal. Appl. 22, 997–1013 (2001)

Davis, T.A., Hager, W.W.: Row modification of a sparse Cholesky factorization. SIAM J. Matrix Anal. Appl. 26, 621–639 (2005)

Hammarling, S., Lucas, C.: Updating the QR factorization and the least squares problem. Tech. rep., The University of Manchester, http://www.manchester.ac.uk/mims/eprints (2008)

Olsson, O., Ivarsson, T.: Using the QR factorization to swiftly upyear least squares problems. Thesis report, Centre for Mathematical Sciences. The Faculty of Engineering at Lund University LTH (2014)

Pothen, A., Fan, C.J.: Computing the block triangular form of a sparse matrix. ACM Trans. Math. Software 16, 303–324 (1990)

Saad, Y.: ILUT: A dual threshold incomplete LU factorization. Numer. Linear Algebra Appl. 1(4), 387–402 (1994)

Saad, Y.: Iterative Methods for Sparse Linear Systems. PWS Publishing Co., Boston (1996)

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