159 search results - page 16 / 32 » Sparse non-Gaussian component analysis |
127
Voted
ECML
2007
Springer
15 years 6 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...
124
Voted
CIKM
2010
Springer
14 years 11 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...
100
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ICPR
2004
IEEE
16 years 1 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...
108
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TMI
2008
14 years 12 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...
112
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NIPS
2003
15 years 1 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 ...