Dominant subspace and low-rank approximations from block Krylov subspaces without a gap.
Pedro MasseyPublished in: CoRR (2021)
Keyphrases
- low rank approximation
- subspace learning
- linear subspace
- high dimensional data
- low dimensional
- principal component analysis
- low rank
- subspace clusters
- dimensionality reduction
- singular value decomposition
- high dimensional
- manifold learning
- feature space
- data representation
- subspace clustering
- face recognition
- learning algorithm
- semi supervised
- kernel matrix
- sparse coding
- data points
- data sets
- nearest neighbor
- sparse representation
- pattern recognition
- iterative algorithms
- eigendecomposition
- input space
- kernel function
- spectral clustering
- metric learning
- data dependent
- dimension reduction
- image segmentation
- adjacency matrix
- feature selection
- linear discriminant analysis