Tensor Rank and the Ill-Posedness of the Best Low-Rank Approximation Problem.
Vin de SilvaLek-Heng LimPublished in: SIAM J. Matrix Anal. Appl. (2008)
Keyphrases
- low rank approximation
- frobenius norm
- singular value decomposition
- low rank
- low rank matrix approximation
- subspace learning
- spectral clustering
- kernel matrix
- high order
- iterative algorithms
- dimensionality reduction
- latent semantic indexing
- nonnegative matrix factorization
- reconstruction error
- data dependent
- adjacency matrix
- singular values
- higher order
- machine learning
- clustering algorithm
- diffusion tensor
- least squares
- semi supervised
- matrix completion
- pattern recognition