Subspace-Orbit Randomized - Based Decomposition for Low-Rank Matrix Approximations.
Maboud F. KalooraziRodrigo C. de LamarePublished in: EUSIPCO (2018)
Keyphrases
- low rank matrix
- approximation methods
- matrix approximation
- low rank
- high dimensional data
- singular value decomposition
- convex optimization
- sparse matrix
- eigendecomposition
- rank minimization
- low dimensional
- matrix factorization
- principal component analysis
- dimensionality reduction
- tensor decomposition
- high order
- least squares
- high dimensional
- feature extraction
- semi supervised
- feature space
- machine learning
- data analysis
- data mining
- data matrix
- pairwise
- singular values
- similarity measure
- subspace learning
- kernel matrix
- linear combination
- principal components
- missing data