Approximating Matrix Eigenvalues by Subspace Iteration with Repeated Random Sparsification
Work
Year: 2022
Type: article
Abstract: Traditional numerical methods for calculating matrix eigenvalues are prohibitively expensive for high-dimensional problems. Iterative random sparsification methods allow for the estimation of a single... more
Institutions Columbia University, Courant Institute of Mathematical Sciences, New York University, Flatiron Health (United States)
Cites: 70
Cited by: 3
Related to: 10
FWCI: 0.542
Citation percentile (by year/subfield): 58.55
Topic: Matrix Theory and Algorithms
Subfield: Computational Theory and Mathematics
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
Funders Office of Science, Office of Advanced Cyberinfrastructure, Division of Mathematical Sciences
Grant IDS DE-SC0020427, OAC-1547580, DMS-1646339