Speeding up k-means by approximating Euclidean distances via block vectors.
Thomas BotteschThomas BühlerMarkus KächelePublished in: ICML (2016)
Keyphrases
- euclidean distance
- k means
- feature vectors
- distance measure
- similarity measure
- image space
- distance metric
- vector space
- data points
- clustering method
- clustering algorithm
- distance function
- euclidean space
- euclidean norm
- geodesic distance
- data clustering
- dimensionality reduction
- hierarchical clustering
- feature extraction
- pairwise distances
- cluster analysis
- cluster centroids
- high dimensional
- spectral clustering
- feature space
- dynamic time warping
- multidimensional scaling
- maximum likelihood
- training data
- decision trees