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