A Computational Study of Using Black-box QR Solvers for Large-scale Sparse-dense Linear Least Squares Problems
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Publication:5066598
DOI10.1145/3494527OpenAlexW3115361341WikidataQ113268482 ScholiaQ113268482MaRDI QIDQ5066598
Publication date: 29 March 2022
Published in: ACM Transactions on Mathematical Software (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1145/3494527
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Cites Work
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- Splitting dense columns in sparse linear systems
- Numerical study on incomplete orthogonal factorization preconditioners
- Modified incomplete orthogonal factorization methods using Givens rotations
- Preconditioning techniques for nonsymmetric and indefinite linear systems
- Parallel solution of sparse linear least squares problems on distributed-memory multiprocessors
- Solution of sparse linear least squares problems using Givens rotations
- Separators and structure prediction in sparse orthogonal factorization
- Matrix enlarging methods and their application
- Partitioning mathematical programs for parallel solution
- A Schur complement approach to preconditioning sparse linear least-squares problems with some dense rows
- Solution of sparse rectangular systems using LSQR and Craig
- CUTEst: a constrained and unconstrained testing environment with safe threads for mathematical optimization
- A class of incomplete orthogonal factorization methods. II: Implemetation and results
- Detecting ``dense columns in interior point methods for linear programs
- Matrix stretching for sparse least squares problems
- Fine-Grained Multithreading for the Multifrontal $QR$ Factorization of Sparse Matrices
- Algorithm 915, SuiteSparseQR
- LSMR: An Iterative Algorithm for Sparse Least-Squares Problems
- The State-of-the-Art of Preconditioners for Sparse Linear Least-Squares Problems
- MIQR: A Multilevel Incomplete QR Preconditioner for Large Sparse Least‐Squares Problems
- Using Perturbed $QR$ Factorizations to Solve Linear Least-Squares Problems
- A Storage-Efficient Algorithm for Finding the Regularized Solution of a Large, Inconsistent System of Equations
- LSQR: An Algorithm for Sparse Linear Equations and Sparse Least Squares
- Some Extensions of an Algorithm for Sparse Linear Least Squares Problems
- CIMGS: An Incomplete Orthogonal FactorizationPreconditioner
- Algorithm 980
- Solving Mixed Sparse-Dense Linear Least-Squares Problems by Preconditioned Iterative Methods
- Accelerating the Solution of Linear Systems by Iterative Refinement in Three Precisions
- Permuting Sparse Rectangular Matrices into Block-Diagonal Form
- Strengths and Limitations of Stretching for Least-squares Problems with Some Dense Rows
- Incomplete Methods for Solving $A^T Ax = b$
- Sparse Stretching for Solving Sparse-Dense Linear Least-Squares Problems
- HSL_MI28
- Algorithm 836
- Iterative refinement of linear least squares solutions I
- Three-Precision GMRES-Based Iterative Refinement for Least Squares Problems
- A class of incomplete orthogonal factorization methods. I: Methods and theories
