543 search results - page 29 / 109 » Nonlinear principal component analysis of noisy data |
ISBI
2004
IEEE
14 years 8 months ago
2004
IEEE
In this paper, we introduce the use of nonlinear dimension reduction for the analysis of functional neuroimaging datasets. Using a Laplacian Embedding approach, we show the power ...
JMLR
2008
13 years 7 months ago
2008
We study a generative model in which hidden causes combine competitively to produce observations. Multiple active causes combine to determine the value of an observed variable thr...
SDM
2010
SIAM
13 years 6 months ago
2010
SIAM
A popular approach for dimensionality reduction and data analysis is principal component analysis (PCA). A limiting factor with PCA is that it does not inform us on which of the o...
ICML
2007
IEEE
14 years 8 months ago
2007
IEEE
In this paper we investigate the regularization property of Kernel Principal Component Analysis (KPCA), by studying its application as a preprocessing step to supervised learning ...
CSDA
2008
13 years 7 months ago
2008
The purpose of this paper is to forecast the time evolution of a binary response variable from an associated continuous time series observed only at discrete time points that usual...