Single-Pass PCA of Large High-Dimensional Data.
Wenjian YuYu GuJian LiShenghua LiuYaohang LiPublished in: CoRR (2017)
Keyphrases
- single pass
- high dimensional data
- dimensionality reduction
- principal component analysis
- low dimensional
- high dimensional
- linear discriminant analysis
- dimension reduction
- lower dimensional
- variable weighting
- high dimensions
- principal components analysis
- subspace clustering
- high dimensionality
- data sets
- data points
- feature space
- input space
- original data
- feature extraction
- locally linear embedding
- data distribution
- principal components
- nearest neighbor
- pattern recognition
- manifold learning
- subspace learning
- data analysis
- low rank
- similarity search
- dimensional data
- high dimensional datasets
- sparse representation
- clustering high dimensional data
- singular value decomposition
- covariance matrix
- euclidean distance
- nonlinear dimensionality reduction
- high dimensional data sets
- dimensionality reduction methods
- discriminant analysis
- kernel pca
- high dimensional spaces
- small sample size
- face images
- feature vectors
- neural network