11 search results - page 1 / 3 » Semi-Supervised Maximum Margin Clustering with Pairwise Cons... |
TKDE
2012
11 years 6 months ago
2012
—The pairwise constraints specifying whether a pair of samples should be grouped together or not have been successfully incorporated into the conventional clustering methods such...
SDM
2004
SIAM
13 years 5 months ago
2004
SIAM
Semi-supervised clustering uses a small amount of supervised data to aid unsupervised learning. One typical approach specifies a limited number of must-link and cannotlink constra...
JMLR
2010
12 years 11 months ago
2010
In this paper, we present an overview of generalized expectation criteria (GE), a simple, robust, scalable method for semi-supervised training using weakly-labeled data. GE fits m...
SDM
2008
SIAM
13 years 5 months ago
2008
SIAM
The recent years have witnessed a surge of interests of semi-supervised clustering methods, which aim to cluster the data set under the guidance of some supervisory information. U...
ICPR
2010
IEEE
13 years 11 months ago
2010
IEEE
This paper introduces a semi-supervised distance metric learning algorithm which uses pair-wise equivalence (similarity and dissimilarity) constraints to improve the original dist...