Regularized Computation of Approximate Pseudoinverse of Large Matrices Using Low-Rank Tensor Train Decompositions.
Namgil LeeAndrzej CichockiPublished in: SIAM J. Matrix Anal. Appl. (2016)
Keyphrases
- low rank
- pseudo inverse
- trace norm
- singular value decomposition
- frobenius norm
- reconstruction error
- least squares
- matrix completion
- matrix decomposition
- high order
- low rank matrix
- tensor decomposition
- ridge regression
- covariance matrix
- matrix factorization
- convex optimization
- data matrix
- singular values
- dimensionality reduction
- linear combination
- missing data
- kernel matrix
- low rank approximation
- tensor factorization
- higher order
- norm minimization
- multi task
- semi supervised
- high dimensional data
- principal component analysis
- data points
- objective function
- small number
- denoising
- machine learning
- sparse representation