A Krylov–Schur approach to the truncated SVD

By Martin Stoll. 2012

50 citations recorded by the source corpus.

Subfields: Atomic and Molecular Physics, and Optics, Computational Theory and Mathematics, Numerical Analysis

View Paper: https://www.semanticscholar.org/paper/27394165626a9aa7bb3bd3db156d649efe4980bf

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Atomic and Molecular Physics, and Optics

1. Hassan Mansour
2. Rajiv Kumar
3. Okan Akalin
4. Felix J. Herrmann
5. Aleksandr Y. Aravkin
6. Curt Da Silva
7. B. Recht

In Computational Theory and Mathematics

1. Hassan Mansour
2. Rajiv Kumar
3. Okan Akalin
4. Felix J. Herrmann
5. Aleksandr Y. Aravkin
6. Curt Da Silva
7. B. Recht

In Numerical Analysis

1. Hassan Mansour
2. Rajiv Kumar
3. Okan Akalin
4. Felix J. Herrmann
5. Aleksandr Y. Aravkin
6. Curt Da Silva
7. B. Recht

Citations in the corpus

• Efficient matrix completion for seismic data reconstruction (2015, methodology): “On the assumption that X is approximately low-rank at a given iteration, other authors such as Stoll (2012) compute a partial SVD using a Krylov approach, which is still cost-prohibitive for large matrices.”