1051 search results - page 71 / 211 » An algorithm for the principal component analysis of large d... |
ICCV
2007
IEEE
14 years 2 months ago
2007
IEEE
Dimensionality reduction plays a fundamental role in data processing, for which principal component analysis (PCA) is widely used. In this paper, we develop the Laplacian PCA (LPC...
ICDAR
2009
IEEE
13 years 5 months ago
2009
IEEE
We report an automatic feature discovery method that achieves results comparable to a manually chosen, larger feature set on a document image content extraction problem: the locat...
ICML
2005
IEEE
14 years 9 months ago
2005
IEEE
Recently, several manifold learning algorithms have been proposed, such as ISOMAP (Tenenbaum et al., 2000), Locally Linear Embedding (Roweis & Saul, 2000), Laplacian Eigenmap ...
NIPS
2008
13 years 9 months ago
2008
We analyse matching pursuit for kernel principal components analysis (KPCA) by proving that the sparse subspace it produces is a sample compression scheme. We show that this bound...
CBSE
2005
Springer
14 years 1 months ago
2005
Springer
Abstract. Searching and subsequently selecting reusable components from component repositories has become a key impediment for not only component-based development but also for ach...