59 search results - page 9 / 12 » Sparse Higher-Order Principal Components Analysis |
KDD
2001
ACM
14 years 11 months ago
2001
ACM
Random projections have recently emerged as a powerful method for dimensionality reduction. Theoretical results indicate that the method preserves distances quite nicely; however,...
ICANN
2009
Springer
14 years 5 months ago
2009
Springer
In this paper the sparse coding principle is employed for the representation of multimodal image data, i.e. image intensity and range. We estimate an image basis for frontal face i...
ICML
2008
IEEE
14 years 11 months ago
2008
IEEE
We study the problem of finding the dominant eigenvector of the sample covariance matrix, under additional constraints on the vector: a cardinality constraint limits the number of...
JMLR
2010
13 years 9 months ago
2010
Sparse coding—that is, modelling data vectors as sparse linear combinations of basis elements—is widely used in machine learning, neuroscience, signal processing, and statisti...
ICPR
2010
IEEE
14 years 26 days ago
2010
IEEE
In this paper we investigate the usage of random ortho-projections in the compression of sparse feature vectors. The study is carried out by evaluating the compressed features in ...