Computing Selected Eigenvalues of Sparse Unsymmetric Matrices Using Subspace Iteration.
Iain S. DuffJennifer A. ScottPublished in: ACM Trans. Math. Softw. (1993)
Keyphrases
- eigendecomposition
- covariance matrices
- singular value decomposition
- high dimensional
- principal components
- covariance matrix
- sparse matrix
- eigenvalues and eigenvectors
- singular vectors
- symmetric matrices
- feature space
- principal component analysis
- singular values
- coefficient matrix
- sparse data
- low rank representation
- low dimensional
- correlation matrix
- spectral clustering
- compressive sensing
- low rank approximation
- dimensionality reduction
- kernel matrix
- low rank matrices
- subspace learning
- basis vectors
- projection matrix
- least squares
- low rank
- semi supervised
- affinity matrix
- input data
- random projections
- high dimensional data