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ICCV
2007
IEEE
14 years 6 months ago
Locally Smooth Metric Learning with Application to Image Retrieval
In this paper, we propose a novel metric learning method based on regularized moving least squares. Unlike most previous metric learning methods which learn a global Mahalanobis d...
Dit-Yan Yeung, Hong Chang
PR
2006
164views more  PR 2006»
13 years 4 months ago
Locally linear metric adaptation with application to semi-supervised clustering and image retrieval
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...
Hong Chang, Dit-Yan Yeung
PR
2006
141views more  PR 2006»
13 years 4 months ago
Relaxational metric adaptation and its application to semi-supervised clustering and content-based image retrieval
The performance of many supervised and unsupervised learning algorithms is very sensitive to the choice of an appropriate distance metric. Previous work in metric learning and ada...
Hong Chang, Dit-Yan Yeung, William K. Cheung
CVPR
2008
IEEE
14 years 6 months ago
Rank-based distance metric learning: An application to image retrieval
We present a novel approach to learn distance metric for information retrieval. Learning distance metric from a number of queries with side information, i.e., relevance judgements...
Jung-Eun Lee, Rong Jin, Anil K. Jain
ECCV
2008
Springer
14 years 6 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