403 search results - page 29 / 81 » Metric and Kernel Learning Using a Linear Transformation |
142
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WEBI
2010
Springer
14 years 11 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...
132
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SBRN
2008
IEEE
15 years 8 months ago
2008
IEEE
The design of an autonomous navigation system for mobile robots can be a tough task. Noisy sensors, unstructured environments and unpredictability are among the problems which mus...
149
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PSIVT
2009
Springer
15 years 8 months ago
2009
Springer
PCA-SIFT is an extension to SIFT which aims to reduce SIFT’s high dimensionality (128 dimensions) by applying PCA to the gradient image patches. However PCA is not a discriminati...
134
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PE
2010
Springer
15 years 8 days ago
2010
Springer
Solution of large sparse linear fixed-point problems lies at the heart of many important performance analysis calculations. These calculations include steady-state, transient and...
149
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GECCO
2006
Springer
15 years 5 months ago
2006
Springer
In this paper we embed evolutionary computation into statistical learning theory. First, we outline the connection between large margin optimization and statistical learning and s...