-Complexity Low-Rank Approximation SVD for Massive Matrix in Tensor Train Format.
Jung-Chun ChiChiao-En ChenYuan-Hao HuangPublished in: ICASSP (2023)
Keyphrases
- low rank approximation
- singular value decomposition
- singular vectors
- low rank matrix approximation
- low rank
- frobenius norm
- subspace learning
- dimensionality reduction
- singular values
- latent semantic indexing
- low rank matrices
- spectral clustering
- reconstruction error
- tensor factorization
- kernel matrix
- adjacency matrix
- least squares
- dimension reduction
- data dependent
- high order
- iterative algorithms
- low rank matrix
- tensor decomposition
- missing data
- higher order
- matrix completion