98 search results - page 11 / 20 » On Point Sampling Versus Space Sampling for Dimensionality R... |
VISUALIZATION
2005
IEEE
14 years 1 months ago
2005
IEEE
This paper presents a novel approach for surface reconstruction from point clouds. The proposed technique is general in the sense that it naturally handles both manifold and non-m...
ICPR
2008
IEEE
14 years 2 months ago
2008
IEEE
For a finite set of points lying on a lower dimensional manifold embedded in a high-dimensional data space, algorithms have been developed to study the manifold structure. Howeve...
COLT
2008
Springer
13 years 9 months ago
2008
Springer
A Hilbert space embedding for probability measures has recently been proposed, with applications including dimensionality reduction, homogeneity testing and independence testing. ...
PR
2008
13 years 7 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...
CVPR
2007
IEEE
14 years 1 months ago
2007
IEEE
Manifold learning methods are promising data analysis tools. However, if we locate a new test sample on the manifold, we have to find its embedding by making use of the learned e...