SeekAView: An intelligent dimensionality reduction strategy for navigating high-dimensional data spaces.
Josua KrauseAritra DasguptaJean-Daniel FeketeEnrico BertiniPublished in: LDAV (2016)
Keyphrases
- high dimensional data
- dimensionality reduction
- low dimensional
- high dimensionality
- high dimensional
- subspace clustering
- principal component analysis
- original data
- nearest neighbor
- data sets
- nonlinear dimensionality reduction
- linear discriminant analysis
- data points
- input space
- manifold learning
- subspace learning
- high dimensions
- pattern recognition
- dimension reduction
- feature extraction
- latent space
- lower dimensional
- similarity search
- feature space
- low rank
- feature selection
- dimensional data
- preprocessing step
- clustering high dimensional data
- principal components
- sparse representation
- metric learning
- data representation
- random projections
- euclidean distance
- high dimensional spaces
- dimensionality reduction methods
- locally linear embedding
- high dimensional datasets
- data analysis
- high dimensional data sets
- input data
- image data
- neural network