28 search results - page 1 / 6 » Constrained Laplacian Eigenmap for dimensionality reduction |
IJON
2010
13 years 3 months ago
2010
ICML
2007
IEEE
14 years 6 months ago
2007
IEEE
Non-linear dimensionality reduction of noisy data is a challenging problem encountered in a variety of data analysis applications. Recent results in the literature show that spect...
ICPR
2010
IEEE
13 years 7 months ago
2010
IEEE
—A novel non-linear dimensionality reduction method, called Temporal Laplacian Eigenmaps, is introduced to process efficiently time series data. In this embedded-based approach,...
ICIP
2010
IEEE
13 years 3 months ago
2010
IEEE
Many classes of image data span a low dimensional nonlinear space embedded in the natural high dimensional image space. We adopt and generalize a recently proposed dimensionality ...
AUSAI
2006
Springer
13 years 9 months ago
2006
Springer
In this paper, we propose the Kernel Laplacian Eigenmaps for nonlinear dimensionality reduction. This method can be extended to any structured input beyond the usual vectorial data...