24 search results - page 2 / 5 » Spectral methods for semi-supervised manifold learning |
CVPR
2008
IEEE
14 years 7 months ago
2008
IEEE
Linear Discriminant Analysis (LDA), which works by maximizing the within-class similarity and minimizing the between-class similarity simultaneously, is a popular dimensionality r...
TKDE
2012
11 years 7 months ago
2012
—The pairwise constraints specifying whether a pair of samples should be grouped together or not have been successfully incorporated into the conventional clustering methods such...
CVPR
2008
IEEE
14 years 7 months ago
2008
IEEE
Given a finite number of data points sampled from a low-dimensional manifold embedded in a high dimensional space together with the parameter vectors for a subset of the data poin...
ICASSP
2009
IEEE
13 years 11 months ago
2009
IEEE
Diffusion Maps (DiffMaps) has recently provided a general framework that unites many other spectral manifold learning algorithms, including Laplacian Eigenmaps, and it has become ...
KDD
2006
ACM
14 years 5 months ago
2006
ACM
Kernel machines have been shown as the state-of-the-art learning techniques for classification. In this paper, we propose a novel general framework of learning the Unified Kernel ...