50 search results - page 3 / 10 » Graph Embedding and Extensions: A General Framework for Dime... |
IJON
2010
13 years 3 months ago
2010
Graph construction plays a key role on learning algorithms based on graph Laplacian. However, the traditional graph construction approaches of -neighborhood and k-nearest-neighbor...
TNN
2008
13 years 6 months ago
2008
Abstract--High-dimensional data are common in many domains, and dimensionality reduction is the key to cope with the curse-of-dimensionality. Linear discriminant analysis (LDA) is ...
PRL
2010
13 years 4 months ago
2010
In this paper, our main contribution is a framework for the automatic configuration of any spectral dimensionality reduction methods. This is achieved, first, by introducing the m...
ICCV
2007
IEEE
14 years 8 months ago
2007
IEEE
Invariant feature descriptors such as SIFT and GLOH have been demonstrated to be very robust for image matching and visual recognition. However, such descriptors are generally par...
ICMCS
2005
IEEE
13 years 12 months ago
2005
IEEE
Semi-definite Embedding (SDE) has been a recently proposed to maximize the sum of pair wise squared distances between outputs while the input data and outputs are locally isometri...