576 search results - page 31 / 116 » Structured metric learning for high dimensional problems |
102
Voted
NIPS
2001
14 years 11 months ago
2001
Drawing on the correspondence between the graph Laplacian, the Laplace-Beltrami operator on a manifold, and the connections to the heat equation, we propose a geometrically motiva...
102
Voted
WEBI
2010
Springer
14 years 7 months ago
2010
Springer
High-dimensional data usually incur learning deficiencies and computational difficulties. We present a novel semi-supervised dimensionality reduction technique that embeds high-dim...
79
Voted
ICML
2009
IEEE
15 years 10 months ago
2009
IEEE
Despite popular belief, boosting algorithms and related coordinate descent methods are prone to overfitting. We derive modifications to AdaBoost and related gradient-based coordin...
MICCAI
2008
Springer
15 years 11 months ago
2008
Springer
We study the problem of classifying an autistic group from controls using structural image data alone, a task that requires a clinical interview with a psychologist. Because of the...
117
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CVPR
2010
IEEE
15 years 1 months ago
2010
IEEE
A clustering framework within the sparse modeling and dictionary learning setting is introduced in this work. Instead of searching for the set of centroid that best fit the data, ...