
doi: 10.1145/5925.5932
In solving large sparse linear least squares problems A x ≃ b, several different numeric methods involve computing the same upper triangular factor R of A . It is of interest to be able to compute the nonzero structure of R , given only the structure of A . The solution to this problem comes from the theory of matchings in bipartite graphs. The structure of A is modeled with a bipartite graph, and it is shown how the rows and columns of A can be rearranged into a structure from which the structure of its upper triangular factor can be correctly computed. Also, a new method for solving sparse least squares problems, called block back-substitution, is presented. This method assures that no unnecessary space is allocated for fill, and that no unnecessary space is needed for intermediate fill.
Computational methods for sparse matrices, least squares, Numerical solutions to overdetermined systems, pseudoinverses, bipartite graphs, orthogonal factorization, matching, sparse matrices, Givens rotations, block triangular form, fill, Orthogonalization in numerical linear algebra
Computational methods for sparse matrices, least squares, Numerical solutions to overdetermined systems, pseudoinverses, bipartite graphs, orthogonal factorization, matching, sparse matrices, Givens rotations, block triangular form, fill, Orthogonalization in numerical linear algebra
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