352 search results - page 1 / 71 » A local search approximation algorithm for k-means clusterin... |
ISAAC
2005
Springer
14 years 4 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
13 years 5 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 8 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 10 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 11 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 ...