733 search results - page 19 / 147 » Learning Riemannian Metrics |
79
Voted
3DIM
2003
IEEE
15 years 2 months ago
2003
IEEE
Due to their general and robust formulation deformable models offer a very appealing approach to 3D image segmentation. However there is a trade-off between model genericity, mode...
82
Voted
ECCV
2008
Springer
15 years 11 months ago
2008
Springer
Distance metric learning has been widely investigated in machine learning and information retrieval. In this paper, we study a particular content-based image retrieval application ...
94
Voted
CVPR
2007
IEEE
15 years 11 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
14 years 9 months ago
2006
Relevant component analysis (RCA) is a recently proposed metric learning method for semi-supervised learning applications. It is a simple and efficient method that has been applie...
90
Voted
ACL
2010
14 years 7 months ago
2010
We initiate a study comparing effectiveness of the transformed spaces learned by recently proposed supervised, and semisupervised metric learning algorithms to those generated by ...