159 search results - page 16 / 32 » Sparse non-Gaussian component analysis |
144
Voted
ECML
2007
Springer
15 years 9 months ago
2007
Springer
Abstract. Principal component analysis (PCA) is a well-known classical data analysis technique. There are a number of algorithms for solving the problem, some scaling better than o...
144
Voted
CIKM
2010
Springer
15 years 1 months ago
2010
Springer
Low-dimensional topic models have been proven very useful for modeling a large corpus of documents that share a relatively small number of topics. Dimensionality reduction tools s...
115
Voted
ICPR
2004
IEEE
16 years 3 months ago
2004
IEEE
Statistical methods, such as independent component analysis, have been successful in learning local low-level features from natural image data. Here we extend these methods for le...
127
Voted
TMI
2008
15 years 2 months ago
2008
A method is presented for the analysis of dynamic positron emission tomography (PET) data using sparse Bayesian learning. Parameters are estimated in a compartmental framework usin...
129
Voted
NIPS
2003
15 years 4 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 ...