70 search results - page 3 / 14 » Multiple Kernel Learning for Dimensionality Reduction |
ICCV
2009
IEEE
15 years 1 months ago
2009
IEEE
We present a manifold learning approach to dimensionality
reduction that explicitly models the manifold as a mapping
from low to high dimensional space. The manifold is
represen...
ICASSP
2011
IEEE
13 years 8 days ago
2011
IEEE
Recently, in generic object recognition research, a classification technique based on integration of image features is garnering much attention. However, with a classifying techn...
ICCV
2009
IEEE
15 years 1 months ago
2009
IEEE
We propose an unconventional but highly effective approach
to robust fitting of multiple structures by using statistical
learning concepts. We design a novel Mercer kernel
for t...
IJCAI
2003
13 years 10 months ago
2003
We equate nonlinear dimensionality reduction (NLDR) to graph embedding with side information about the vertices, and derive a solution to either problem in the form of a kernel-ba...
ACCV
2006
Springer
14 years 9 days ago
2006
Springer
Abstract. In this paper, we propose a new method for image classification, in which matrix based kernel features are designed to capture the multiple similarities between images in...