1825 search results - page 29 / 365 » Local Dimensionality Reduction |
ICML
2009
IEEE
15 years 10 months ago
2009
IEEE
In this paper, we introduce a generic framework for semi-supervised kernel learning. Given pairwise (dis-)similarity constraints, we learn a kernel matrix over the data that respe...
AAAI
2010
14 years 11 months ago
2010
Multi-instance learning deals with problems that treat bags of instances as training examples. In single-instance learning problems, dimensionality reduction is an essential step ...
88
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CVPR
2006
IEEE
15 years 11 months ago
2006
IEEE
Dimensionality reduction involves mapping a set of high dimensional input points onto a low dimensional manifold so that "similar" points in input space are mapped to ne...
109
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VISSYM
2003
14 years 11 months ago
2003
Traditional visualization techniques for multidimensional data sets, such as parallel coordinates, glyphs, and scatterplot matrices, do not scale well to high numbers of dimension...
CVPR
2008
IEEE
15 years 11 months ago
2008
IEEE
Linear Discriminant Analysis (LDA), which works by maximizing the within-class similarity and minimizing the between-class similarity simultaneously, is a popular dimensionality r...