Journal
SIAM JOURNAL ON SCIENTIFIC COMPUTING
Volume 40, Issue 2, Pages A1149-A1170Publisher
SIAM PUBLICATIONS
DOI: 10.1137/17M1123080
Keywords
Jacobi-Davidson; eigenvalue problem; low-rank approximation; Riemannian optimization
Categories
Funding
- RFBR [16-31-00372-mol-a, 16-31-60095-mol-a-dk]
Ask authors/readers for more resources
In this work we generalize the Jacobi-Davidson method to the case when eigenvector can be reshaped into a low-rank matrix. In this setting the proposed method inherits advantages of the original Jacobi-Davidson method, has lower complexity and requires less storage. We also introduce low-rank version of the Rayleigh quotient iteration which naturally arises in the Jacobi-Davidson method.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available
Share Paper
