91 search results - page 7 / 19 » Kernel Dimensionality Reduction for Supervised Learning |
115
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ICCV
2009
IEEE
16 years 5 months ago
2009
IEEE
Mean shift clustering is a powerful unsupervised data
analysis technique which does not require prior knowledge
of the number of clusters, and does not constrain the shape
of th...
101
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IJCAI
2007
15 years 1 months ago
2007
Kernel based nonlinear Feature Extraction (KFE) or dimensionality reduction is a widely used pre-processing step in pattern classification and data mining tasks. Given a positive...
125
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ICCV
2005
IEEE
16 years 2 months ago
2005
IEEE
In recent years Kernel Principal Component Analysis (Kernel PCA) has gained much attention because of its ability to capture nonlinear image features, which are particularly impor...
PAMI
2007
14 years 12 months ago
2007
—Over the past few decades, a large family of algorithms—supervised or unsupervised; stemming from statistics or geometry theory—has been designed to provide different soluti...
104
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PR
2010
14 years 10 months ago
2010
We develop a supervised dimensionality reduction method, called Lorentzian Discriminant Projection (LDP), for feature extraction and classification. Our method represents the str...