On Coresets for Fair Clustering in Metric and Euclidean Spaces and Their Applications.
Sayan BandyapadhyayFedor V. FominKirill SimonovPublished in: ICALP (2021)
Keyphrases
- euclidean space
- riemannian manifolds
- metric space
- multi dimensional scaling
- data points
- wide class
- distance metric
- geodesic distance
- euclidean distance
- vector space
- shape analysis
- higher dimensional
- clustering algorithm
- k means
- pairwise distances
- square root
- metric learning
- spectral clustering
- range queries
- machine learning
- neural network