Dimensionality Reduction for the Sum-of-Distances Metric.
Zhili FengPraneeth KachamDavid P. WoodruffPublished in: ICML (2021)
Keyphrases
- dimensionality reduction
- euclidean distance
- distance function
- metric learning
- distance measure
- distance metric
- data points
- low dimensional
- principal component analysis
- hausdorff distance
- geodesic distance
- high dimensional data
- high dimensional
- dimensionality reduction methods
- pattern recognition
- embedding space
- high dimensionality
- metric space
- dissimilarity measure
- pairwise distances
- triangular inequality
- manifold learning
- manhattan distance
- data representation
- number of distance computations
- distance computation
- structure preserving
- random projections
- euclidean space
- feature extraction
- feature space
- linear dimensionality reduction
- multidimensional scaling
- similarity search
- weighted sum
- input space
- multi dimensional scaling
- data sets
- absolute difference
- triangle inequality
- nonlinear dimensionality reduction
- principal components
- intrinsic dimensionality
- text categorization
- linear discriminant analysis
- kernel pca
- kernel learning
- pattern recognition and machine learning
- image processing
- feature selection
- machine learning