189 search results - page 20 / 38 » Unsupervised Nonlinear Manifold Learning |
CVPR
2006
IEEE
15 years 2 days ago
2006
IEEE
Dimensionality reduction involves mapping a set of high dimensional input points onto a low dimensional manifold so that "similar" points in input space are mapped to ne...
ICPR
2008
IEEE
14 years 11 months ago
2008
IEEE
Embedding images into a low dimensional space has a wide range of applications: visualization, clustering, and pre-processing for supervised learning. Traditional dimension reduct...
PAMI
2006
13 years 10 months ago
2006
High dimensional structured data such as text and images is often poorly understood and misrepresented in statistical modeling. The standard histogram representation suffers from ...
ICPR
2010
IEEE
13 years 9 months ago
2010
IEEE
Abstract—Learning dynamical systems is one of the important problems in many fields. In this paper, we present an algorithm for learning non-linear dynamical systems which works...
ICCV
2007
IEEE
14 years 4 months ago
2007
IEEE
Dimensionality reduction plays a fundamental role in data processing, for which principal component analysis (PCA) is widely used. In this paper, we develop the Laplacian PCA (LPC...