Estimating dependency and significance for high-dimensional data.
Michael SiracusaKinh TieuAlexander T. IhlerJohn W. Fisher IIIAlan S. WillskyPublished in: ICASSP (5) (2005)
Keyphrases
- high dimensional data
- low dimensional
- dimensionality reduction
- high dimensionality
- high dimensional
- nearest neighbor
- data sets
- high dimensions
- data analysis
- subspace clustering
- input space
- similarity search
- dimension reduction
- clustering high dimensional data
- original data
- data points
- lower dimensional
- sparse representation
- manifold learning
- complex data
- data distribution
- high dimensional spaces
- input data
- high dimensional datasets
- linear discriminant analysis
- nonlinear dimensionality reduction
- data mining
- text data
- high dimensional data sets
- pattern recognition
- locally linear embedding
- data structure
- knowledge discovery
- small sample size
- principal component analysis
- database