766 search results - page 36 / 154 » Clustering high dimensional data using subspace and projecte... |
CVPR
2009
IEEE
15 years 3 months ago
2009
IEEE
We propose a method based on sparse representation
(SR) to cluster data drawn from multiple low-dimensional
linear or affine subspaces embedded in a high-dimensional
space. Our ...
SDM
2003
SIAM
13 years 10 months ago
2003
SIAM
A major challenge in document clustering is the extremely high dimensionality. For example, the vocabulary for a document set can easily be thousands of words. On the other hand, ...
ICDM
2006
IEEE
14 years 2 months ago
2006
IEEE
High dimensionality remains a significant challenge for document clustering. Recent approaches used frequent itemsets and closed frequent itemsets to reduce dimensionality, and to...
ECML
2006
Springer
14 years 10 days ago
2006
Springer
Spectral clustering has attracted much research interest in recent years since it can yield impressively good clustering results. Traditional spectral clustering algorithms first s...
JMLR
2010
13 years 3 months ago
2010
We derive PAC-Bayesian generalization bounds for supervised and unsupervised learning models based on clustering, such as co-clustering, matrix tri-factorization, graphical models...