55 search results - page 1 / 11 » On Relevant Dimensions in Kernel Feature Spaces |
101
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JMLR
2008
14 years 10 months ago
2008
We show that the relevant information of a supervised learning problem is contained up to negligible error in a finite number of leading kernel PCA components if the kernel matche...
ICML
2007
IEEE
15 years 11 months ago
2007
IEEE
We study the problem of discovering a manifold that best preserves information relevant to a nonlinear regression. Solving this problem involves extending and uniting two threads ...
101
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JMLR
2010
14 years 8 months ago
2010
Convolution kernels for trees provide simple means for learning with tree-structured data. The computation time of tree kernels is quadratic in the size of the trees, since all pa...
96
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ICIP
2003
IEEE
15 years 11 months ago
2003
IEEE
Relevance feedback is an attractive approach to developing flexible metrics for content-based retrieval in image and video databases. Large image databases require an index struct...
ICML
2010
IEEE
14 years 11 months ago
2010
IEEE
Dimension reduction is popular for learning predictive models in high-dimensional spaces. It can highlight the relevant part of the feature space and avoid the curse of dimensiona...