33 search results - page 1 / 7 » Laplacian Eigenmaps and Spectral Techniques for Embedding an... |
NIPS
2001
13 years 6 months ago
2001
Drawing on the correspondence between the graph Laplacian, the Laplace-Beltrami operator on a manifold, and the connections to the heat equation, we propose a geometrically motiva...
CVPR
2008
IEEE
14 years 6 months ago
2008
IEEE
This paper examines the problem of extracting lowdimensional manifold structure given millions of highdimensional face images. Specifically, we address the computational challenge...
FTML
2010
13 years 3 months ago
2010
We give a tutorial overview of several geometric methods for dimension reduction. We divide the methods into projective methods and methods that model the manifold on which the da...
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...