1244 search results - page 153 / 249 » The many faces of interpolation |
184
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CVPR
2007
IEEE
16 years 8 months ago
2007
IEEE
Dimensionality reduction is an important issue when facing high-dimensional data. For supervised dimensionality reduction, Linear Discriminant Analysis (LDA) is one of the most po...
186
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CVPR
2007
IEEE
16 years 8 months ago
2007
IEEE
A novel algorithm called Average Neighborhood Margin Maximization (ANMM) is proposed for supervised linear feature extraction. For each data point, ANMM aims at pulling the neighb...
164
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CVPR
2008
IEEE
16 years 8 months ago
2008
IEEE
Many applications in computer vision and pattern recognition involve drawing inferences on certain manifoldvalued parameters. In order to develop accurate inference algorithms on ...
173
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CVPR
2008
IEEE
16 years 8 months ago
2008
IEEE
Linear Discriminant Analysis (LDA), which works by maximizing the within-class similarity and minimizing the between-class similarity simultaneously, is a popular dimensionality r...
173
click to vote
CVPR
2008
IEEE
16 years 8 months ago
2008
IEEE
Linear Discriminant Analysis (LDA) is one of the wellknown methods for supervised dimensionality reduction. Over the years, many LDA-based algorithms have been developed to cope w...