Computing Low-Rank Approximations of Large-Scale Matrices with the Tensor Network Randomized SVD.
Kim BatselierWenjian YuLuca DanielNgai WongPublished in: SIAM J. Matrix Anal. Appl. (2018)
Keyphrases
- low rank approximation
- singular value decomposition
- low rank matrix approximation
- dimensionality reduction
- low rank
- singular values
- spectral clustering
- reconstruction error
- subspace learning
- least squares
- matrix decomposition
- matrix completion
- higher order
- latent semantic indexing
- data dependent
- iterative algorithms
- adjacency matrix
- kernel matrix
- community structure
- data matrix
- complex networks
- network structure
- nonnegative matrix factorization
- high order
- sparse representation