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» Information-theoretic metric learning
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DAGM
2007
Springer
14 years 3 months ago
The Minimum Volume Ellipsoid Metric
We propose an unsupervised “local learning” algorithm for learning a metric in the input space. Geometrically, for a given query point, the algorithm finds the minimum volume ...
Karim T. Abou-Moustafa, Frank P. Ferrie
ECML
2006
Springer
14 years 1 months ago
Subspace Metric Ensembles for Semi-supervised Clustering of High Dimensional Data
A critical problem in clustering research is the definition of a proper metric to measure distances between points. Semi-supervised clustering uses the information provided by the ...
Bojun Yan, Carlotta Domeniconi
PR
2006
164views more  PR 2006»
13 years 9 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
NIPS
2004
13 years 11 months ago
Object Classification from a Single Example Utilizing Class Relevance Metrics
We describe a framework for learning an object classifier from a single example. This goal is achieved by emphasizing the relevant dimensions for classification using available ex...
Michael Fink 0002
ICML
2007
IEEE
14 years 10 months ago
Optimal dimensionality of metric space for classification
In many real-world applications, Euclidean distance in the original space is not good due to the curse of dimensionality. In this paper, we propose a new method, called Discrimina...
Wei Zhang, Xiangyang Xue, Zichen Sun, Yue-Fei Guo,...