New Probabilistic Bounds on Eigenvalues and Eigenvectors of Random Kernel Matrices.
Nima ReyhaniHideitsu HinoRicardo VigárioPublished in: UAI (2011)
Keyphrases
- eigenvalues and eigenvectors
- kernel matrices
- generalization bounds
- kernel methods
- covariance matrix
- kernel matrix
- lower bound
- low rank
- kernel function
- learning theory
- probabilistic model
- upper bound
- worst case
- generalization ability
- kernel learning
- data dependent
- reproducing kernel hilbert space
- adjacency matrix
- training data
- semi supervised
- sample size
- linear combination
- model selection