24 search results - page 2 / 5 » Constrained Clustering by Spectral Kernel Learning |
ECML
2007
Springer
13 years 11 months ago
2007
Springer
Abstract. Clustering has recently enjoyed progress via spectral methods which group data using only pairwise affinities and avoid parametric assumptions. While spectral clustering ...
ICML
2004
IEEE
14 years 6 months ago
2004
IEEE
In this paper we show that many kernel methods can be adapted to deal with indefinite kernels, that is, kernels which are not positive semidefinite. They do not satisfy Mercer...
ICML
2007
IEEE
14 years 6 months ago
2007
IEEE
We propose a family of clustering algorithms based on the maximization of dependence between the input variables and their cluster labels, as expressed by the Hilbert-Schmidt Inde...
ECML
2003
Springer
13 years 10 months ago
2003
Springer
We consider the topographic clustering task and focus on the problem of its evaluation, which enables to perform model selection: topographic clustering algorithms, from the origin...
JMLR
2010
13 years 3 months ago
2010
A large number of learning algorithms, for example, spectral clustering, kernel Principal Components Analysis and many manifold methods are based on estimating eigenvalues and eig...