A greedy algorithm for computing eigenvalues of a symmetric matrix with localized eigenvectors.
Taylor M. HernandezRoel Van BeeumenMark A. CaprioChao YangPublished in: Numer. Linear Algebra Appl. (2021)
Keyphrases
- greedy algorithm
- covariance matrix
- symmetric matrix
- eigenvalue decomposition
- objective function
- covariance matrices
- symmetric matrices
- principal component analysis
- greedy algorithms
- dynamic programming
- sample size
- greedy strategy
- worst case
- eigendecomposition
- principal components
- singular value decomposition
- pseudo inverse
- spectral clustering
- blind source separation
- least squares
- influence spread
- semidefinite programming
- feature extraction
- laplacian matrix
- low dimensional