-norm principal component analysis for robust subspace factorization.
Chris H. Q. DingDing ZhouXiaofeng HeHongyuan ZhaPublished in: ICML (2006)
Keyphrases
- principal component analysis
- principal components
- low dimensional
- dimensionality reduction
- singular value decomposition
- feature space
- feature extraction
- covariance matrix
- independent component analysis
- subspace learning
- hilbert space
- lower dimensional
- face recognition
- low rank representation
- dimension reduction
- discriminant analysis
- high dimensional data
- subspace methods
- low rank
- pairwise
- rank minimization
- neural network