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Publication
Existing person re-identification methods conventionally rely on labelled pairwise data to learn a task-specific distance metric for ranking. The value of unlabelled gallery instan...
KDD
2008
ACM
15 years 3 months ago
2008
ACM
The success of popular algorithms such as k-means clustering or nearest neighbor searches depend on the assumption that the underlying distance functions reflect domain-specific n...
ICML
2007
IEEE
15 years 3 months ago
2007
IEEE
Distance metric learning and nonlinear dimensionality reduction are two interesting and active topics in recent years. However, the connection between them is not thoroughly studi...
ECCV
2008
Springer
15 years 5 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 ...
CVPR
2008
IEEE
15 years 5 months ago
2008
IEEE
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...
CVPR
2007
IEEE
15 years 5 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...