31 search results - page 1 / 7 » Kernel k-means: spectral clustering and normalized cuts |
KDD
2004
ACM
14 years 5 months ago
2004
ACM
Kernel k-means and spectral clustering have both been used to identify clusters that are non-linearly separable in input space. Despite significant research, these methods have re...
DIS
2006
Springer
13 years 8 months ago
2006
Springer
Abstract. Clustering algorithms based on a matrix of pairwise similarities (kernel matrix) for the data are widely known and used, a particularly popular class being spectral clust...
PAMI
2007
13 years 4 months ago
2007
—A variety of clustering algorithms have recently been proposed to handle data that is not linearly separable; spectral clustering and kernel k-means are two of the main methods....
ICCV
2005
IEEE
13 years 10 months ago
2005
IEEE
We derive the clustering problem from first principles showing that the goal of achieving a probabilistic, or ”hard”, multi class clustering result is equivalent to the algeb...
JMLR
2012
11 years 7 months ago
2012
An important form of prior information in clustering comes in form of cannot-link and must-link constraints. We present a generalization of the popular spectral clustering techniq...