31 search results - page 2 / 7 » Kernel k-means: spectral clustering and normalized cuts |
KDD
2005
ACM
14 years 5 months ago
2005
ACM
Graph clustering (also called graph partitioning) -- clustering the nodes of a graph -- is an important problem in diverse data mining applications. Traditional approaches involve...
SDM
2007
SIAM
13 years 6 months ago
2007
SIAM
In this paper we formulate spectral clustering in directed graphs as an optimization problem, the objective being a weighted cut in the directed graph. This objective extends seve...
PR
2008
13 years 5 months ago
2008
Clustering algorithms are a useful tool to explore data structures and have been employed in many disciplines. The focus of this paper is the partitioning clustering problem with ...
CVPR
2010
IEEE
13 years 5 months ago
2010
IEEE
We propose a new algorithm for learning kernels for variants of the Normalized Cuts (NCuts) objective – i.e., given a set of training examples with known partitions, how should ...
ICML
2009
IEEE
14 years 6 months ago
2009
IEEE
We present a generalized version of spectral clustering using the graph p-Laplacian, a nonlinear generalization of the standard graph Laplacian. We show that the second eigenvecto...