191 search results - page 12 / 39 » Generalized Power Method for Sparse Principal Component Anal... |
ICIP
2009
IEEE
15 years 10 months ago
2009
IEEE
Recently morphological diversity and sparsity have emerged as new and effective sources of diversity for Blind Source Separation. Based on these new concepts, novel methods such a...
ICCV
2009
IEEE
14 years 7 months ago
2009
IEEE
The use of Mercer kernel methods in statistical learning theory provides for strong learning capabilities, as seen in kernel principal component analysis and support vector machin...
98
Voted
ICPR
2010
IEEE
14 years 11 months 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 ...
SIAMJO
2011
14 years 4 months ago
2011
In this paper we define semidefinite packing programs and describe an algorithm to approximately solve these problems. Semidefinite packing programs arise in many applications s...
92
Voted
NIPS
2003
14 years 11 months ago
2003
In this paper, sparse representation (factorization) of a data matrix is first discussed. An overcomplete basis matrix is estimated by using the K−means method. We have proved ...