2312 search results - page 119 / 463 » On the Dimensionality of Face Space |
171
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COMSIS
2010
15 years 3 months ago
2010
Dimensionality reduction is an important preprocessing step in high-dimensional data analysis without losing intrinsic information. The problem of semi-supervised nonlinear dimensi...
163
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IV
2007
IEEE
16 years 21 days ago
2007
IEEE
High-dimensional data is, by its nature, difficult to visualise. Many current techniques involve reducing the dimensionality of the data, which results in a loss of information. ...
157
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ICCV
2009
IEEE
16 years 11 months ago
2009
IEEE
Low-rank approximation of image collections (e.g., via
PCA) is a popular tool in many areas of computer vision.
Yet, surprisingly little is known justifying the observation
that...
186
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CVPR
2004
IEEE
16 years 8 months ago
2004
IEEE
Classifying high-dimensional numerical data is a very challenging problem. In high dimensional feature spaces, the performance of supervised learning methods suffer from the curse...
181
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ICDM
2002
IEEE
15 years 11 months ago
2002
IEEE
Clustering large data sets of high dimensionality has always been a serious challenge for clustering algorithms. Many recently developed clustering algorithms have attempted to ad...