181 search results - page 8 / 37 » Graph Embedding: A General Framework for Dimensionality Redu... |
CVPR
1997
IEEE
16 years 1 months ago
1997
IEEE
A general geometrical framework for image processing is presented. We consider intensity images as surfaces in the (x I) space. The image is thereby a two dimensional surface in t...
124
Voted
PAMI
2011
14 years 6 months ago
2011
—In solving complex visual learning tasks, adopting multiple descriptors to more precisely characterize the data has been a feasible way for improving performance. The resulting ...
AAAI
2007
15 years 2 months ago
2007
Recently the problem of dimensionality reduction has received a lot of interests in many fields of information processing. We consider the case where data is sampled from a low d...
81
Voted
ICIP
2010
IEEE
14 years 9 months ago
2010
IEEE
Many classes of image data span a low dimensional nonlinear space embedded in the natural high dimensional image space. We adopt and generalize a recently proposed dimensionality ...
ICML
2009
IEEE
16 years 17 days ago
2009
IEEE
We present a unified framework for learning link prediction and edge weight prediction functions in large networks, based on the transformation of a graph's algebraic spectru...