Asymptotic error bounds for kernel-based Nyström low-rank approximation matrices.
Lo-Bin ChangZhidong BaiSu-Yun HuangChii-Ruey HwangPublished in: J. Multivar. Anal. (2013)
Keyphrases
- error bounds
- low rank approximation
- low rank matrix approximation
- worst case
- singular value decomposition
- kernel matrix
- kernel methods
- low rank
- spectral clustering
- subspace learning
- theoretical analysis
- matrix completion
- nonnegative matrix factorization
- adjacency matrix
- iterative algorithms
- reconstruction error
- latent semantic indexing
- singular values
- low rank matrices
- support vector
- support vector machine
- data dependent
- matrix factorization
- upper bound
- approximation algorithms
- linear combination
- least squares
- positive definite
- eigendecomposition
- low rank matrix
- data representation
- high dimensional data
- np hard
- lower bound