109 search results - page 6 / 22 » SRDA: An Efficient Algorithm for Large-Scale Discriminant An... |
100
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TNN
2008
14 years 9 months ago
2008
Abstract--High-dimensional data are common in many domains, and dimensionality reduction is the key to cope with the curse-of-dimensionality. Linear discriminant analysis (LDA) is ...
CIVR
2008
Springer
14 years 11 months ago
2008
Springer
As the consequence of semantic gap, visual similarity does not guarantee semantic similarity, which in general is conflicting with the inherent assumption of many generativebased ...
BMCBI
2010
14 years 9 months ago
2010
Background: The amount of available biological information is rapidly increasing and the focus of biological research has moved from single components to networks and even larger ...
TKDE
2008
14 years 9 months ago
2008
Linear and kernel discriminant analyses are popular approaches for supervised dimensionality reduction. Uncorrelated and regularized discriminant analyses have been proposed to ove...
101
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PR
2008
14 years 9 months ago
2008
7 Linear discriminant analysis (LDA) is a dimension reduction method which finds an optimal linear transformation that maximizes the class separability. However, in undersampled p...