Low-Rank Factorizations in Data Sparse Hierarchical Algorithms for Preconditioning Symmetric Positive Definite Matrices
Work
Year: 2018
Type: article
Abstract: We consider the problem of choosing low-rank factorizations in data sparse matrix approximations for preconditioning large-scale symmetric positive definite (SPD) matrices. These approximations are me... more
Institution Numerical Algorithms Group (United Kingdom)
Cites: 22
Cited by: 6
Related to: 10
FWCI: 0.692
Citation percentile (by year/subfield): 66.93
Topic: Matrix Theory and Algorithms
Subfield: Computational Theory and Mathematics
Field: Computer Science
Domain: Physical Sciences
Sustainable Development Goal Decent work and economic growth
Open Access status: green