Stretching is a sparse matrix technique that improves sparsity by making the least-squares problem larger. We show that standard stretching can still result in ...

SPARSE STRETCHING FOR SOLVING SPARSE-DENSE LINEAR LEAST-SQUARES. PROBLEMS. JENNIFER SCOTT∗ AND MIROSLAV TUMA†. Abstract. Large-scale linear least-squares ...

Stretching is a sparse matrix technique that improves sparsity by making the least-squares problem larger. We show that standard stretching can still result in ...

Sparse stretching for solving sparse-dense linear least-squares problems. SIAM J. on Scientific Computing, to appear, 2019. [8] J. A. Scott and M. Tuma ...

Mar 26, 2019 · Stretching is a sparse matrix technique that improves sparsity by making the least-squares problem larger. We show that standard stretching can ...

Sparse Stretching for Solving Sparse-Dense Linear Least-Squares Problems. Scott, Jennifer A. ;; Tůma, Miroslav. Abstract. Publication: SIAM Journal on ...

This motivates us to propose a new sparse stretching strategy that performs the stretching so as to limit the fill in the normal matrix and its Cholesky factor.

Sparse stretching is designed to limit the amount of fill within the stretched normal matrix and hence within the subsequent Cholesky factorization. While ...

Abstract. The efficient solution of large linear least-squares problems in which the system matrix A contains rows with very different densities is ...

Abstract. We recently introduced a sparse stretching strategy for handling dense rows that can arise in large-scale linear least-squares problems and make ...