The Curse Revisited: When are Distances Informative for the Ground Truth in Noisy High-Dimensional Data?
Robin VandaeleBo KangTijl De BieYvan SaeysPublished in: AISTATS (2022)
Keyphrases
- high dimensional data
- ground truth
- dimensionality reduction
- nearest neighbor
- high dimensional
- high dimensionality
- low dimensional
- similarity search
- dimension reduction
- distance function
- high dimensions
- data analysis
- subspace clustering
- data sets
- data points
- euclidean distance
- input space
- data distribution
- distance measure
- noisy data
- sparse representation
- linear discriminant analysis
- input data
- high dimensional datasets
- distance computation
- original data
- lower dimensional
- manifold learning
- high dimensional spaces
- small sample size
- high dimensional data sets
- high dimensional feature spaces
- dimensional data
- training set
- locally linear embedding
- pattern recognition