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» Learning Riemannian Metrics
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3DIM
2003
IEEE
14 years 24 days ago
Deformable Model with Adaptive Mesh and Automated Topology Changes
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...
Jacques-Olivier Lachaud, Benjamin Taton
ECCV
2008
Springer
14 years 9 months ago
Output Regularized Metric Learning with Side Information
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 ...
Wei Liu, Steven C. H. Hoi, Jianzhuang Liu
CVPR
2007
IEEE
14 years 9 months ago
Adaptive Distance Metric Learning for Clustering
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...
Jieping Ye, Zheng Zhao, Huan Liu
PR
2006
76views more  PR 2006»
13 years 7 months ago
Extending the relevant component analysis algorithm for metric learning using both positive and negative equivalence constraints
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...
Dit-Yan Yeung, Hong Chang
ACL
2010
13 years 5 months ago
Learning Better Data Representation Using Inference-Driven Metric Learning
We initiate a study comparing effectiveness of the transformed spaces learned by recently proposed supervised, and semisupervised metric learning algorithms to those generated by ...
Paramveer S. Dhillon, Partha Pratim Talukdar, Koby...