287 search results - page 6 / 58 » Optimal Solutions for Sparse Principal Component Analysis |
NIPS
2008
14 years 11 months ago
2008
Recently, supervised dimensionality reduction has been gaining attention, owing to the realization that data labels are often available and indicate important underlying structure...
110
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ECML
2007
Springer
15 years 3 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...
CIKM
2010
Springer
14 years 8 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
14 years 9 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
14 years 9 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...