352 search results - page 1 / 71 » A local search approximation algorithm for k-means clusterin... |
ISAAC
2005
Springer
13 years 10 months ago
2005
Springer
In this paper we study the k-means clustering problem. It is well-known that the general version of this problem is NP-hard. Numerous approximation algorithms have been proposed fo...
MLDM
2010
Springer
12 years 11 months ago
2010
Springer
In this paper we study the k-means clustering problem. It is well-known that the general version of this problem is NP-hard. Numerous approximation algorithms have been proposed fo...
FOCS
2010
IEEE
13 years 2 months ago
2010
IEEE
We consider k-median clustering in finite metric spaces and k-means clustering in Euclidean spaces, in the setting where k is part of the input (not a constant). For the k-means pr...
COMGEO
2004
ACM
13 years 4 months ago
2004
ACM
In k-means clustering we are given a set of n data points in d-dimensional space d and an integer k, and the problem is to determine a set of k points in d , called centers, to mi...
ICML
2007
IEEE
14 years 5 months ago
2007
IEEE
Although each iteration of the popular kMeans clustering heuristic scales well to larger problem sizes, it often requires an unacceptably-high number of iterations to converge to ...