2 search results - page 1 / 1 » Robust PCA via Outlier Pursuit |
CORR
2010
Springer
13 years 9 months ago
2010
Springer
Singular Value Decomposition (and Principal Component Analysis) is one of the most widely used techniques for dimensionality reduction: successful and efficiently computable, it ...
NIPS
2008
14 years 4 days ago
2008
Kernel Principal Component Analysis (KPCA) is a popular generalization of linear PCA that allows non-linear feature extraction. In KPCA, data in the input space is mapped to highe...