39 search results - page 4 / 8 » Integrating constraints and metric learning in semi-supervis... |
SDM
2009
SIAM
14 years 5 months ago
2009
SIAM
Most datasets in real applications come in from multiple sources. As a result, we often have attributes information about data objects and various pairwise relations (similarity) ...
ICCV
2009
IEEE
15 years 1 months ago
2009
IEEE
Mean shift clustering is a powerful unsupervised data
analysis technique which does not require prior knowledge
of the number of clusters, and does not constrain the shape
of th...
KDD
2008
ACM
14 years 9 months ago
2008
ACM
The success of popular algorithms such as k-means clustering or nearest neighbor searches depend on the assumption that the underlying distance functions reflect domain-specific n...
SDM
2008
SIAM
13 years 10 months ago
2008
SIAM
Although clustering under constraints is a current research topic, a hierarchical setting, in which a hierarchy of clusters is the goal, is usually not considered. This paper trie...
ALT
2003
Springer
14 years 6 days ago
2003
Springer
Abstract. A crucial problem in machine learning is to choose an appropriate representation of data, in a way that emphasizes the relations we are interested in. In many cases this ...