60 search results - page 5 / 12 » Continuous nonlinear dimensionality reduction by kernel Eige... |
172
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CVPR
2009
IEEE
16 years 10 months ago
2009
IEEE
Non-linear dimensionality reductionmethods are powerful techniques to deal with
high-dimensional datasets. However, they often are susceptible to local minima
and perform poorly ...
138
Voted
ICPR
2006
IEEE
16 years 4 months ago
2006
IEEE
1 A kernel determines the inductive bias of a learning algorithm on a specific data set, and it is beneficial to design specific kernel for a given data set. In this work, we propo...
122
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NIPS
2003
15 years 4 months ago
2003
We propose a non-linear Canonical Correlation Analysis (CCA) method which works by coordinating or aligning mixtures of linear models. In the same way that CCA extends the idea of...
110
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CVPR
2008
IEEE
16 years 5 months ago
2008
IEEE
We consider the problem of dimensionality reduction, where given high-dimensional data we want to estimate two mappings: from high to low dimension (dimensionality reduction) and f...
154
Voted
ICCV
2011
IEEE
14 years 3 months ago
2011
IEEE
Non-rigid structure from motion (NRSFM) is a difficult, underconstrained problem in computer vision. The standard approach in NRSFM constrains 3D shape deformation using a linear...