468 search results - page 58 / 94 » Riemannian Manifold Learning |
ICMCS
2009
IEEE
13 years 5 months ago
2009
IEEE
We consider the problem of classification of multiple observations of the same object, possibly under different transformations. We view this problem as a special case of semi-sup...
COLT
1994
Springer
13 years 11 months ago
1994
Springer
We examine the relationship between the VCdimension and the number of parameters of a smoothly parametrized function class. We show that the VC-dimension of such a function class ...
PAMI
2002
13 years 7 months ago
2002
We investigate the use of linear and nonlinear principal manifolds for learning low-dimensional representations for visual recognition. Several leading techniques: Principal Compo...
IJCAI
2007
13 years 9 months ago
2007
Dimensionality reduction is a much-studied task in machine learning in which high-dimensional data is mapped, possibly via a non-linear transformation, onto a low-dimensional mani...
AAAI
2007
13 years 10 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...