Fast Robust Subspace Tracking via PCA in Sparse Data-Dependent Noise.
Namrata VaswaniPraneeth NarayanamurthyPublished in: CoRR (2020)
Keyphrases
- data dependent
- principal component analysis
- high dimensional
- low rank representation
- principal components analysis
- dimensionality reduction
- rank minimization
- robust principal component analysis
- low dimensional
- feature space
- principal components
- sparse pca
- linear subspace
- hash functions
- risk bounds
- low rank
- feature extraction
- face recognition
- random projections
- data sets
- subspace learning
- reproducing kernel hilbert space
- dimension reduction
- subspace methods
- linear discriminant analysis
- covariance matrix
- rademacher complexity
- missing data