On lower bounds for the smallest eigenvalue of a Hermitian positive-definite matrix.
Evan M. MaChristopher J. ZarowskiPublished in: IEEE Trans. Inf. Theory (1995)
Keyphrases
- positive definite
- covariance matrix
- lower bound
- objective function
- upper bound
- fisher information
- kernel function
- sample size
- principal component analysis
- diffusion tensor
- semi parametric
- worst case
- symmetric matrix
- least squares
- geometric structure
- kernel matrix
- symmetric positive definite
- training data
- vc dimension
- pairwise
- support vector