Sampling-based dimension reduction for subspace approximation.
Amit DeshpandeKasturi R. VaradarajanPublished in: STOC (2007)
Keyphrases
- dimension reduction
- low dimensional
- principal component analysis
- high dimensional data
- high dimensional
- feature extraction
- linear projection
- feature space
- dimensionality reduction
- qr decomposition
- high dimensional problems
- feature subspace
- linear discriminant analysis
- lower dimensional
- manifold learning
- discriminative information
- feature selection
- singular value decomposition
- high dimensional data analysis
- principal components
- subspace clustering
- random projections
- high dimensionality
- partial least squares
- monte carlo
- linear subspace
- discriminant analysis
- face recognition
- unsupervised learning
- subspace learning
- data points
- image processing
- nearest neighbor
- cluster analysis
- preprocessing
- data analysis
- original data
- scatter matrices
- sparse representation
- data sets