Coresets for Clustering in Euclidean Spaces: Importance Sampling is Nearly Optimal.
Lingxiao HuangNisheeth K. VishnoiPublished in: CoRR (2020)
Keyphrases
- importance sampling
- euclidean space
- monte carlo
- data points
- particle filter
- markov chain
- riemannian manifolds
- k means
- clustering algorithm
- kalman filter
- shape analysis
- approximate inference
- vector space
- euclidean distance
- particle filtering
- closed form
- dynamic programming
- image processing
- computer vision
- high dimensional data
- model selection