12 search results - page 1 / 3 » Nonlinear Dimension Reduction of fMRI Data: The Laplacian Em... |
ISBI
2004
IEEE
14 years 5 months ago
2004
IEEE
In this paper, we introduce the use of nonlinear dimension reduction for the analysis of functional neuroimaging datasets. Using a Laplacian Embedding approach, we show the power ...
BMCBI
2010
13 years 5 months ago
2010
Background: Visualization of DNA microarray data in two or three dimensional spaces is an important exploratory analysis step in order to detect quality issues or to generate new ...
AUSAI
2006
Springer
13 years 8 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...
ICML
2007
IEEE
14 years 5 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...
ICML
2005
IEEE
14 years 5 months ago
2005
IEEE
Many unsupervised algorithms for nonlinear dimensionality reduction, such as locally linear embedding (LLE) and Laplacian eigenmaps, are derived from the spectral decompositions o...