Unraveling the Veil of Subspace RIP Through Near-Isometry on Subspaces.
Xingyu XuGen LiYuantao GuPublished in: IEEE Trans. Signal Process. (2020)
Keyphrases
- linear subspace
- subspace clusters
- high dimensional data
- low dimensional
- null space
- lower dimensional
- canonical correlations
- grassmann manifold
- principal component analysis
- low rank representation
- subspace clustering
- linear projection
- high dimensional
- subspace analysis
- image space
- dimensionality reduction
- subspace learning
- hilbert space
- vector field
- feature space
- stochastic gradient
- canonical correlation analysis
- arbitrarily oriented
- linear discriminant analysis
- face recognition
- basis vectors
- multiple views
- clustering high dimensional data
- euclidean space
- subspace methods
- data sets
- singular value decomposition
- data points
- dimension reduction
- image set
- feature subspace
- higher dimensional
- face space
- input data
- data analysis
- optimization criterion
- linear combination
- discriminant analysis
- finite dimensional
- principal components
- shape analysis
- multi frame