Dimensionality Reduction for k-Means Clustering and Low Rank Approximation
Author:
Affiliation:
1. Massachusetts Institute of Technology, Cambridge, MA, USA
2. Massachusetts Institute of Technology, Cambrdige, MA, USA
Funder
Defense Advanced Research Projects Agency
National Science Foundation
Air Force Office of Scientific Research
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/2746539.2746569
Reference46 articles.
1. Database-friendly random projections: Johnson-Lindenstrauss with binary coins
2. NP-hardness of Euclidean sum-of-squares clustering
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