91 search results - page 10 / 19 » Non-linear Dimensionality Reduction by Locally Linear Isomap... |
ICPR
2008
IEEE
14 years 1 months ago
2008
IEEE
The locally linear embedding (LLE) algorithm is considered as a powerful method for the problem of nonlinear dimensionality reduction. In this paper, first, a new method called cl...
ICML
2005
IEEE
14 years 8 months ago
2005
IEEE
Recently, several manifold learning algorithms have been proposed, such as ISOMAP (Tenenbaum et al., 2000), Locally Linear Embedding (Roweis & Saul, 2000), Laplacian Eigenmap ...
PAMI
2007
13 years 7 months ago
2007
This paper considers the problem of dimensionality reduction by orthogonal projection techniques. The main feature of the proposed techniques is that they attempt to preserve both...
ICIP
2007
IEEE
13 years 11 months ago
2007
IEEE
This communication deals with data reduction and regression. A set of high dimensional data (e.g., images) usually has only a few degrees of freedom with corresponding variables t...
TNN
2008
13 years 7 months ago
2008
In this paper, a new kernel-based method for data visualization and dimensionality reduction is proposed. A reference point is considered corresponding to additional constraints ta...