22 search results - page 3 / 5 » Spectral Relaxation for K-means Clustering |
DAGM
2011
Springer
12 years 5 months ago
2011
Springer
Many unsupervised learning algorithms make use of kernels that rely on the Euclidean distance between two samples. However, the Euclidean distance is optimal for Gaussian distribut...
COLT
2005
Springer
13 years 11 months ago
2005
Springer
We consider the problem of learning mixtures of distributions via spectral methods and derive a tight characterization of when such methods are useful. Specifically, given a mixt...
ICCV
2003
IEEE
14 years 7 months ago
2003
IEEE
We propose a principled account on multiclass spectral clustering. Given a discrete clustering formulation, we first solve a relaxed continuous optimization problem by eigendecomp...
NIPS
2004
13 years 6 months ago
2004
We show how to build hierarchical, reduced-rank representation for large stochastic matrices and use this representation to design an efficient algorithm for computing the largest...
DIS
2006
Springer
13 years 9 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...