Keywords
Affiliated Institutions
Related Publications
On coresets for k-means and k-median clustering
In this paper, we show the existence of small coresets for the problems of computing k-median and k-means clustering for points in low dimension. In other words, we show that gi...
A local search approximation algorithm for k-means clustering
In k-means clustering we are given a set of n data points in d-dimensional space ℜd and an integer k, and the problem is to determine a set of k points in ℜd, called centers, to...
Approximation schemes for clustering problems
Let k be a fixed integer. We consider the problem of partitioning an input set of points endowed with a distance function into k clusters. We give polynomial time approximation ...
How 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...
How fast is the k-means method?
We present polynomial upper and lower bounds on the number of iterations performed by the k-means method (a.k.a. Lloyd's method) for k-means clustering. Our upper bounds are pol...
Publication Info
- Year
- 2002
- Type
- article
- Volume
- 33
- Issue
- 2
- Pages
- 201-226
- Citations
- 244
- Access
- Closed
External Links
Social Impact
Social media, news, blog, policy document mentions
Citation Metrics
Cite This
Identifiers
- DOI
- 10.1007/s00453-001-0110-y