Matrix Sparsification and the Sparse Null Space Problem.
Lee-Ad GottliebTyler NeylonPublished in: APPROX-RANDOM (2010)
Keyphrases
- null space
- theoretical guarantees
- linear discriminant analysis
- projection matrix
- singular value decomposition
- novelty detection
- principal components
- singular values
- sparse representation
- high dimensional
- scatter matrices
- least squares
- discriminant analysis
- discriminative information
- learning algorithm
- small sample size
- random projections
- dimension reduction
- image processing
- finite dimensional
- natural images
- dimensionality reduction
- intrinsic dimensionality
- worst case
- object recognition
- data sets