403 search results - page 27 / 81 » Metric and Kernel Learning Using a Linear Transformation |
113
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ICCV
2007
IEEE
15 years 8 months ago
2007
IEEE
Dimensionality reduction plays a fundamental role in data processing, for which principal component analysis (PCA) is widely used. In this paper, we develop the Laplacian PCA (LPC...
129
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CVPR
2010
IEEE
15 years 10 months ago
2010
IEEE
Several object categorization algorithms use kernel methods over multiple cues, as they offer a principled approach to combine multiple cues, and to obtain state-of-theart perform...
109
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CORR
2008
Springer
15 years 1 months ago
2008
Springer
Maximum Variance Unfolding (MVU) and its variants have been very successful in embedding data-manifolds in lower dimensionality spaces, often revealing the true intrinsic dimensio...
148
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RIVF
2008
15 years 3 months ago
2008
Complex biological data generated from various experiments are stored in diverse data types in multiple datasets. By appropriately representing each biological dataset as a kernel ...
141
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IJCNN
2007
IEEE
15 years 8 months ago
2007
IEEE
Abstract— The generalised linear model (GLM) is the standard approach in classical statistics for regression tasks where it is appropriate to measure the data misfit using a lik...