A minimum norm approach for low-rank approximations of a matrix.
Achiya DaxPublished in: J. Comput. Appl. Math. (2010)
Keyphrases
- low rank approximation
- singular value decomposition
- minimum norm
- least squares
- low rank
- spectral clustering
- subspace learning
- reconstruction error
- kernel matrix
- iterative algorithms
- adjacency matrix
- dimension reduction
- latent semantic indexing
- image reconstruction
- convex optimization
- linear combination
- dimensionality reduction
- missing data
- signal reconstruction
- matrix factorization
- nonnegative matrix factorization
- computer vision
- kernel methods
- semi supervised