440 search results - page 3 / 88 » Learning the structure of manifolds using random projections |
ADCM
2008
13 years 5 months ago
2008
Learning function relations or understanding structures of data lying in manifolds embedded in huge dimensional Euclidean spaces is an important topic in learning theory. In this ...
CORR
2010
Springer
13 years 5 months ago
2010
Springer
The Random Projection Tree (RPTREE) structures proposed in [1] are space partitioning data structures that automatically adapt to various notions of intrinsic dimensionality of da...
AAAI
2007
13 years 8 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...
GRC
2008
IEEE
13 years 6 months ago
2008
IEEE
Manifold learning can discover the structure of high dimensional data and provides understanding of multidimensional patterns by preserving the local geometric characteristics. Ho...
ICIP
2008
IEEE
14 years 7 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 ...