733 search results - page 19 / 147 » Learning Riemannian Metrics |
116
Voted
3DIM
2003
IEEE
15 years 7 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...
131
Voted
ECCV
2008
Springer
16 years 3 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 ...
132
Voted
CVPR
2007
IEEE
16 years 3 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
15 years 1 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...
131
Voted
ACL
2010
14 years 12 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 ...