91 search results - page 13 / 19 » Kernel Dimensionality Reduction for Supervised Learning |
130
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ISDA
2010
IEEE
15 years 16 days ago
2010
IEEE
Dimensionality reduction and feature selection in particular are known to be of a great help for making supervised learning more effective and efficient. Many different feature sel...
151
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AMC
2011
14 years 6 months ago
2011
：In this paper, a novel supervised dimensionality reduction method is developed based on both the correlation analysis and the idea of large margin learning. The method aims to m...
114
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CVPR
2007
IEEE
16 years 4 months ago
2007
IEEE
The success of tensor-based subspace learning depends heavily on reducing correlations along the column vectors of the mode-k flattened matrix. In this work, we study the problem ...
140
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KDD
2006
ACM
16 years 3 months ago
2006
ACM
Principal component analysis (PCA) has been extensively applied in data mining, pattern recognition and information retrieval for unsupervised dimensionality reduction. When label...
146
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JMLR
2010
14 years 9 months ago
2010
Different aspects of the curse of dimensionality are known to present serious challenges to various machine-learning methods and tasks. This paper explores a new aspect of the dim...