114 search results - page 1 / 23 » Nonlinear adaptive distance metric learning for clustering |
KDD
2007
ACM
14 years 4 months ago
2007
ACM
A good distance metric is crucial for many data mining tasks. To learn a metric in the unsupervised setting, most metric learning algorithms project observed data to a lowdimensio...
CVPR
2007
IEEE
14 years 6 months ago
2007
IEEE
A good distance metric is crucial for unsupervised learning from high-dimensional data. To learn a metric without any constraint or class label information, most unsupervised metr...
PR
2006
13 years 4 months ago
2006
Many computer vision and pattern recognition algorithms are very sensitive to the choice of an appropriate distance metric. Some recent research sought to address a variant of the...
ICMLC
2005
Springer
13 years 10 months ago
2005
Springer
Abstract. Many supervised and unsupervised learning algorithms depend on the choice of an appropriate distance metric. While metric learning for supervised learning tasks has a lon...
PR
2010
13 years 2 months ago
2010
Most existing representative works in semi-supervised clustering do not sufficiently solve the violation problem of pairwise constraints. On the other hand, traditional kernel met...