181 search results - page 1 / 37 » Graph Embedding: A General Framework for Dimensionality Redu... |
PAMI
2007
13 years 10 months ago
2007
—Over the past few decades, a large family of algorithms—supervised or unsupervised; stemming from statistics or geometry theory—has been designed to provide different soluti...
CVPR
2005
IEEE
15 years 26 days ago
2005
IEEE
In the last decades, a large family of algorithms supervised or unsupervised; stemming from statistic or geometry theory have been proposed to provide different solutions to the p...
PAMI
2006
13 years 10 months ago
2006
We provide evidence that non-linear dimensionality reduction, clustering and data set parameterization can be solved within one and the same framework. The main idea is to define ...
NIPS
2008
14 years 8 days ago
2008
In solving complex visual learning tasks, adopting multiple descriptors to more precisely characterize the data has been a feasible way for improving performance. These representa...
NIPS
2001
14 years 6 days 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...