23 search results - page 2 / 5 » On Kernels, Margins, and Low-Dimensional Mappings |
ICCV
2009
IEEE
14 years 9 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...
JMM2
2008
13 years 4 months ago
2008
This paper presents a technique for face recognition which uses wavelet transform to derive desirable facial features. Three level decompositions are used to form the pyramidal mul...
NIPS
2008
13 years 6 months ago
2008
This paper introduces a new approach to constructing meaningful lower dimensional representations of sets of data points. We argue that constraining the mapping between the high a...
KDD
2009
ACM
14 years 5 months ago
2009
ACM
When labeled examples are limited and difficult to obtain, transfer learning employs knowledge from a source domain to improve learning accuracy in the target domain. However, the...
DAGM
2010
Springer
13 years 6 months ago
2010
Springer
Density modeling is notoriously difficult for high dimensional data. One approach to the problem is to search for a lower dimensional manifold which captures the main characteristi...