On the theory and practice of high-dimensional data indexing with iDistance.
Michael A. SchuhRafal A. AngrykPublished in: IEEE BigData (2016)
Keyphrases
- high dimensional data
- dimensionality reduction
- nearest neighbor
- low dimensional
- high dimensional
- high dimensions
- high dimensionality
- data sets
- subspace clustering
- data analysis
- dimension reduction
- input space
- clustering high dimensional data
- sparse representation
- data points
- similarity search
- linear discriminant analysis
- original data
- high dimensional spaces
- manifold learning
- dimensionality curse
- database
- dimensional data
- high dimensional data sets
- variable selection
- lower dimensional
- high dimensional datasets
- neural network
- data distribution
- input data
- nonlinear dimensionality reduction
- indexing techniques
- computer vision
- locally linear embedding
- clustering algorithm