On the computation of few eigenvalues of positive definite Hamiltonian matrices.
Pierluigi AmodioPublished in: Future Gener. Comput. Syst. (2006)
Keyphrases
- positive definite
- positive definite matrices
- covariance matrix
- symmetric matrices
- kernel matrix
- kernel function
- covariance matrices
- geometric structure
- kernel methods
- diffusion tensor
- symmetric positive definite
- semi parametric
- input space
- reproducing kernel hilbert space
- principal component analysis
- feature extraction
- sample size
- sufficient conditions
- least squares