287 search results - page 12 / 58 » Optimal Solutions for Sparse Principal Component Analysis |
IJCNN
2007
IEEE
15 years 3 months ago
2007
IEEE
— To approximate complex data, we propose new type of low-dimensional “principal object”: principal cubic complex. This complex is a generalization of linear and nonlinear pr...
CVPR
2006
IEEE
15 years 11 months ago
2006
IEEE
Linear Discriminant Analysis (LDA) is a well-known and important tool in pattern recognition with potential applications in many areas of research. The most famous and used formul...
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CVPR
2011
IEEE
14 years 5 months ago
2011
IEEE
Exact recovery from contaminated visual data plays an important role in various tasks. By assuming the observed data matrix as the addition of a low-rank matrix and a sparse matri...
NIPS
2007
14 years 11 months ago
2007
We propose a method for reconstruction of human brain states directly from functional neuroimaging data. The method extends the traditional multivariate regression analysis of dis...
JMLR
2010
14 years 8 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...