543 search results - page 64 / 109 » Nonlinear principal component analysis of noisy data |
JMIV
2006
14 years 9 months ago
2006
We present a novel representation of shape for closed contours in R2 or for compact surfaces in R3 explicitly designed to possess a linear structure. This greatly simplifies linear...
SSDBM
2008
IEEE
15 years 4 months ago
2008
IEEE
Abstract. Most correlation clustering algorithms rely on principal component analysis (PCA) as a correlation analysis tool. The correlation of each cluster is learned by applying P...
TNN
2008
14 years 9 months ago
2008
Abstract--Plenty of methods have been proposed in order to discover latent variables (features) in data sets. Such approaches include the principal component analysis (PCA), indepe...
ICMCS
2005
IEEE
15 years 3 months ago
2005
IEEE
In this paper, we propose a novel technique for modelbased recognition of complex object motion trajectories using Gaussian Mixture Models (GMM). We build our models on Principal ...
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This paper studies the effect of covariance regularization for classific ation of high-dimensional data. This is done by fitting a mixture of Gaussians with a regularized covaria...