DiVA: Indexing high-dimensional data by "diving" into vector approximations.
Konstantinos TsakalozosSpiros EvangelatosAlex DelisPublished in: ICME (2011)
Keyphrases
- high dimensional data
- low dimensional
- nearest neighbor
- dimensionality reduction
- high dimensions
- dimensionality curse
- high dimensionality
- data sets
- high dimensional
- subspace clustering
- data points
- data analysis
- input space
- similarity search
- original data
- manifold learning
- high dimensional spaces
- dimension reduction
- lower dimensional
- data distribution
- vector space
- high dimensional datasets
- low rank
- clustering high dimensional data
- feature vectors
- text data
- sparse representation
- human motion
- linear discriminant analysis
- indexing structure
- input data
- database
- feature selection
- subspace learning
- small sample size
- computer vision
- indexing techniques
- pattern recognition
- neural network
- training set