1187 search results - page 22 / 238 » The Generalized Dimensionality Reduction Problem |
87
Voted
ICIP
2005
IEEE
15 years 11 months ago
2005
IEEE
We study the use of kernel subspace methods that learn low-dimensional subspace representations for classification tasks. In particular, we propose a new method called kernel weigh...
ICANN
2003
Springer
15 years 2 months ago
2003
Springer
The problem of category learning has been traditionally investigated by employing disembodied categorization models. One of the basic tenets of embodied cognitive science states th...
SIAMMAX
2010
14 years 4 months ago
2010
Linear Discriminant Analysis (LDA) is one of the most popular approaches for feature extraction and dimension reduction to overcome the curse of the dimensionality of the high-dime...
PKDD
2010
Springer
14 years 7 months ago
2010
Springer
The foremost nonlinear dimensionality reduction algorithms provide an embedding only for the given training data, with no straightforward extension for test points. This shortcomin...
69
Voted
COMSIS
2010
14 years 7 months ago
2010
Dimensionality reduction is an important preprocessing step in high-dimensional data analysis without losing intrinsic information. The problem of semi-supervised nonlinear dimensi...