A sparse grid based method for generative dimensionality reduction of high-dimensional data.
Bastian BohnJochen GarckeMichael GriebelPublished in: J. Comput. Phys. (2016)
Keyphrases
- high dimensional data
- dimensionality reduction
- dimension reduction
- high dimensional
- high dimensionality
- subspace learning
- low dimensional
- high dimensional spaces
- principal components
- data sets
- data points
- similarity search
- feature extraction
- input space
- metric learning
- random projections
- dimensionality reduction methods
- locally linear embedding
- high dimensional datasets
- clustering high dimensional data
- sparse representation
- multi dimensional
- principal component analysis
- nearest neighbor
- real world