k-means++: the advantages of careful seeding
The k-means method is a widely used clustering technique that seeks to minimize the average squared distance between points in the same cluster. Although it offers no accuracy g...
Publications
3 shownHow slow is the <i>k</i> -means method?
The k-means method is an old but popular clustering algorithm known for its observed speed and its simplicity. Until recently, however, no meaningful theoretical bounds were kno...
Worst-case and Smoothed Analysis of the ICP Algorithm, with an Application to the k-means Method
We show a worst-case lower bound and a smoothed upper bound on the number of iterations performed by the iterative closest point (ICP) algorithm. First proposed by Besl and McKa...
Frequent Co-Authors
Researcher Info
- h-index
- 3
- Publications
- 3
- Citations
- 6,636
- Institution
- Stanford University
External Links
Identifiers
- ORCID
- 0000-0003-0235-1624
Impact Metrics
h-index
3
h-index: Number of publications with at least h citations each.