Preconditioning Linear Least-Squares Problems by Identifying a Basis Matrix
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Publication:3449796
DOI10.1137/140975358zbMath1325.65041OpenAlexW4299432195MaRDI QIDQ3449796
Publication date: 30 October 2015
Published in: SIAM Journal on Scientific Computing (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1137/140975358
Computational methods for sparse matrices (65F50) Numerical solutions to overdetermined systems, pseudoinverses (65F20) Graphs and linear algebra (matrices, eigenvalues, etc.) (05C50) Direct numerical methods for linear systems and matrix inversion (65F05) Preconditioners for iterative methods (65F08)
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Rectangular maximum-volume submatrices and their applications, Preconditioners for Krylov subspace methods: An overview, Implementation of an interior point method with basis preconditioning, On maximum residual block and two-step Gauss-Seidel algorithms for linear least-squares problems, On maximum volume submatrices and cross approximation for symmetric semidefinite and diagonally dominant matrices, Subset selection for matrices with fixed blocks, Preconditioning of Linear Least Squares by Robust Incomplete Factorization for Implicitly Held Normal Equations, Some algorithms for maximum volume and cross approximation of symmetric semidefinite matrices
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Cites Work
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