879 search results - page 128 / 176 » Forecasting high-dimensional data |
ICCV
2007
IEEE
15 years 11 months ago
2007
IEEE
Most existing subspace analysis-based tracking algorithms utilize a flattened vector to represent a target, resulting in a high dimensional data learning problem. Recently, subspa...
ICCV
2001
IEEE
15 years 11 months ago
2001
IEEE
Principal Component Analysis (PCA) has been widely used for the representation of shape, appearance, and motion. One drawback of typical PCA methods is that they are least squares...
ICPR
2004
IEEE
15 years 10 months ago
2004
IEEE
In this paper, we propose an unsupervised approach to select representative face samples (models) from raw videos and build an appearance-based face recognition system. The approa...
ICML
2009
IEEE
15 years 10 months ago
2009
IEEE
Sparsity is a desirable property in high dimensional learning. The 1-norm regularization can lead to primal sparsity, while max-margin methods achieve dual sparsity. Combining the...
ICML
2009
IEEE
15 years 10 months ago
2009
IEEE
Despite popular belief, boosting algorithms and related coordinate descent methods are prone to overfitting. We derive modifications to AdaBoost and related gradient-based coordin...