Balancing Geometry and Density: Path Distances on High-Dimensional Data.
Anna LittleDaniel McKenzieJames MurphyPublished in: CoRR (2020)
Keyphrases
- high dimensional data
- dimensionality reduction
- nearest neighbor
- low dimensional
- high dimensional
- high dimensionality
- similarity search
- data sets
- data analysis
- geodesic distance
- data points
- subspace clustering
- high dimensions
- distance function
- euclidean distance
- manifold learning
- dimension reduction
- data distribution
- shortest path
- low dimensional manifolds
- sparse representation
- original data
- linear discriminant analysis
- distance measure
- high dimensional spaces
- lower dimensional
- clustering high dimensional data
- text data
- input space
- dimensional data
- underlying manifold
- nonlinear dimensionality reduction
- subspace learning
- image data
- locally linear embedding
- high dimensional datasets
- k means
- distance computation
- small sample size
- similarity measure
- image processing