49 search results - page 4 / 10 » Dimensionality Reduction by Learning an Invariant Mapping |
JMM2
2008
13 years 7 months ago
2008
Unsupervised or Self-Organized learning algorithms have become very popular for discovery of significant patterns or features in the input data. The three prominent algorithms name...
ICPR
2008
IEEE
14 years 8 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...
IVC
2007
13 years 7 months ago
2007
Many natural image sets are samples of a low-dimensional manifold in the space of all possible images. When the image data set is not a linear combination of a small number of bas...
CVPR
2007
IEEE
14 years 9 months ago
2007
IEEE
A large family of algorithms for dimensionality reduction end with solving a Trace Ratio problem in the form of arg maxW Tr(WT SpW)/Tr(WT SlW)1 , which is generally transformed in...
ECCV
2006
Springer
14 years 9 months ago
2006
Springer
Abstract. There has been growing interest in developing nonlinear dimensionality reduction algorithms for vision applications. Although progress has been made in recent years, conv...