Subspace-restricted singular value decompositions for linear discrete ill-posed problems.
Michiel E. HochstenbachLothar ReichelPublished in: J. Comput. Appl. Math. (2010)
Keyphrases
- singular values
- singular vectors
- singular value decomposition
- dimensionality reduction
- principal component analysis
- linear subspace
- low rank
- high dimensional data
- grassmann manifold
- hilbert space
- high dimensional
- feature extraction
- digital images
- continuous variables
- closed form
- subspace clustering
- convex optimization
- data sets
- least squares
- data analysis
- image processing
- neural network