59 search results - page 4 / 12 » Sparse Higher-Order Principal Components Analysis |
ECML
2007
Springer
14 years 13 days 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...
CIKM
2010
Springer
13 years 4 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...
BMCBI
2010
13 years 6 months ago
2010
Background: Principal component analysis (PCA) has gained popularity as a method for the analysis of highdimensional genomic data. However, it is often difficult to interpret the ...
BMCBI
2010
13 years 6 months ago
2010
Background: As a novel cancer diagnostic paradigm, mass spectroscopic serum proteomic pattern diagnostics was reported superior to the conventional serologic cancer biomarkers. Ho...
IJON
2006
13 years 6 months ago
2006
In this paper, it is shown that Independent Component Analysis (ICA) of sparse signals (sparse ICA) can be seen as a cluster-wise Principal Component Analysis (PCA). Consequently,...