129 search results - page 21 / 26 » Clustering-based locally linear embedding |
NIPS
2008
13 years 9 months ago
2008
We continue our study of online prediction of the labelling of a graph. We show a fundamental limitation of Laplacian-based algorithms: if the graph has a large diameter then the ...
IJIT
2004
13 years 9 months ago
2004
In this contribution, the use of a new genetic operator is proposed. The main advantage of using this operator is that it is able to assist the evolution procedure to converge fast...
NIPS
1997
13 years 9 months ago
1997
Nonlinear dimensionality reduction is formulated here as the problem of trying to find a Euclidean feature-space embedding of a set of observations that preserves as closely as p...
ICML
2010
IEEE
13 years 8 months ago
2010
IEEE
Existing approaches to analyzing the asymptotics of graph Laplacians typically assume a well-behaved kernel function with smoothness assumptions. We remove the smoothness assumpti...
FTML
2010
13 years 6 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...