88 search results - page 11 / 18 » Distance Preserving Dimension Reduction for Manifold Learnin... |
CVPR
2008
IEEE
15 years 11 months ago
2008
IEEE
We consider the problem of dimensionality reduction, where given high-dimensional data we want to estimate two mappings: from high to low dimension (dimensionality reduction) and f...
DAGM
2006
Springer
15 years 1 months ago
2006
Springer
Abstract. Isomap is a highly popular manifold learning and dimensionality reduction technique that effectively performs multidimensional scaling on estimates of geodesic distances....
ACCV
2009
Springer
15 years 4 months ago
2009
Springer
This paper develops a supervised dimensionality reduction method, Lorentzian Discriminant Projection (LDP), for discriminant analysis and classification. Our method represents the...
ECCV
2004
Springer
15 years 11 months ago
2004
Springer
Abstract. Dimensionality reduction is an essential aspect of visual processing. Traditionally, linear dimensionality reduction techniques such as principle components analysis have...
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JMLR
2010
14 years 4 months ago
2010
The problems of dimension reduction and inference of statistical dependence are addressed by the modeling framework of learning gradients. The models we propose hold for Euclidean...