Subspace-Orbit Randomized Decomposition for Low-Rank Matrix Approximations.
Maboud Farzaneh KalooraziRodrigo C. de LamarePublished in: IEEE Trans. Signal Process. (2018)
Keyphrases
- low rank matrix
- approximation methods
- matrix approximation
- low rank
- singular value decomposition
- matrix factorization
- high dimensional data
- convex optimization
- rank minimization
- principal component analysis
- sparse matrix
- eigendecomposition
- low dimensional
- dimensionality reduction
- tensor decomposition
- missing data
- high dimensional
- least squares
- subspace learning
- pattern recognition
- matrix completion
- feature maps
- data points
- singular values
- belief state
- semi supervised
- function approximation
- feature extraction
- principal components