Large-Scale Nyström Kernel Matrix Approximation Using Randomized SVD.
Mu LiWei BiJames T. KwokBao-Liang LuPublished in: IEEE Trans. Neural Networks Learn. Syst. (2015)
Keyphrases
- matrix approximation
- low rank matrix approximation
- low rank approximation
- kernel matrix
- singular value decomposition
- least squares
- low rank
- kernel methods
- matrix completion
- theoretical guarantees
- low rank matrix
- feature space
- approximation error
- kernel function
- subspace learning
- singular values
- maximum entropy
- positive definite
- metric learning
- reconstruction error
- iterative algorithms
- spectral clustering
- input space
- eigendecomposition
- adjacency matrix
- dimensionality reduction
- principal component analysis
- latent semantic indexing
- special case
- nearest neighbor
- support vector
- low dimensional
- reproducing kernel hilbert space
- nonnegative matrix factorization
- training samples
- matrix factorization
- manifold learning