434 search results - page 30 / 87 » Dimensionality Reduction of Clustered Data Sets |
116
click to vote
AAAI
2007
15 years 3 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...
105
click to vote
ICIP
2008
IEEE
16 years 3 months ago
2008
IEEE
In this paper, we focus on the use of random projections as a dimensionality reduction tool for sampled manifolds in highdimensional Euclidean spaces. We show that geodesic paths ...
115
click to vote
IDEAL
2004
Springer
15 years 7 months ago
2004
Springer
Microarray datasets are often too large to visualise due to the high dimensionality. The self-organising map has been found useful to analyse massive complex datasets. It can be us...
117
click to vote
IVC
2007
15 years 1 months ago
2007
Many natural image sets are samples of a low-dimensional manifold in the space of all possible images. When the image data set is not a linear combination of a small number of bas...
151
Voted
ICCV
2007
IEEE
16 years 3 months ago
2007
IEEE
In this paper, we propose a novel metric learning method based on regularized moving least squares. Unlike most previous metric learning methods which learn a global Mahalanobis d...