5 search results - page 1 / 1 » Manifold Constrained Finite Gaussian Mixtures |
IWANN
2005
Springer
13 years 10 months ago
2005
Springer
In many practical applications, the data is organized along a manifold of lower dimension than the dimension of the embedding space. This additional information can be used when le...
ICANN
2005
Springer
13 years 10 months ago
2005
Springer
In many data mining applications, the data manifold is of lower dimension than the dimension of the input space. In this paper, it is proposed to take advantage of this additional ...
TSP
2010
12 years 11 months ago
2010
Nonparametric Bayesian methods are employed to constitute a mixture of low-rank Gaussians, for data x RN that are of high dimension N but are constrained to reside in a low-dimen...
ICCS
2007
Springer
13 years 10 months ago
2007
Springer
We present a Dynamic Data Driven Application System (DDDAS) to track 2D shapes across large pose variations by learning non-linear shape manifold as overlapping, piecewise linear s...
JMLR
2010
12 years 11 months ago
2010
Appropriate selection of the kernel function, which implicitly defines the feature space of an algorithm, has a crucial role in the success of kernel methods. In this paper, we co...