70 search results - page 3 / 14 » Multiple Kernel Learning for Dimensionality Reduction |
ICCV
2009
IEEE
14 years 10 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
12 years 9 months 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
14 years 10 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 6 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
13 years 9 months 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...