Orthogonalization Via Deflation: A Minimum Norm Approach for Low-Rank Approximations of a Matrix.
Achiya DaxPublished in: SIAM J. Matrix Anal. Appl. (2008)
Keyphrases
- low rank approximation
- singular value decomposition
- minimum norm
- least squares
- low rank
- subspace learning
- kernel matrix
- adjacency matrix
- spectral clustering
- iterative algorithms
- image reconstruction
- reconstruction error
- nonnegative matrix factorization
- latent semantic indexing
- dimensionality reduction
- missing data
- dimension reduction
- face recognition
- high resolution
- eigendecomposition
- positive definite
- clustering algorithm
- small number
- kernel function