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APWEB
2005
Springer
14 years 1 months ago
An Incremental Subspace Learning Algorithm to Categorize Large Scale Text Data
The dramatic growth in the number and size of on-line information sources has fueled increasing research interest in the incremental subspace learning problem. In this paper, we pr...
Jun Yan, QianSheng Cheng, Qiang Yang, Benyu Zhang
BMCBI
2011
12 years 11 months ago
Study of large and highly stratified population datasets by combining iterative pruning principal component analysis and STRUCTU
Background: The ever increasing sizes of population genetic datasets pose great challenges for population structure analysis. The Tracy-Widom (TW) statistical test is widely used ...
Tulaya Limpiti, Apichart Intarapanich, Anunchai As...
COLT
2010
Springer
13 years 6 months ago
Principal Component Analysis with Contaminated Data: The High Dimensional Case
We consider the dimensionality-reduction problem (finding a subspace approximation of observed data) for contaminated data in the high dimensional regime, where the number of obse...
Huan Xu, Constantine Caramanis, Shie Mannor
CSDA
2004
105views more  CSDA 2004»
13 years 7 months ago
Computational aspects of algorithms for variable selection in the context of principal components
Variable selection consists in identifying a k-subset of a set of original variables that is optimal for a given criterion of adequate approximation to the whole data set. Several...
Jorge Cadima, J. Orestes Cerdeira, Manuel Minhoto
BMCBI
2005
201views more  BMCBI 2005»
13 years 7 months ago
Principal component analysis for predicting transcription-factor binding motifs from array-derived data
Background: The responses to interleukin 1 (IL-1) in human chondrocytes constitute a complex regulatory mechanism, where multiple transcription factors interact combinatorially to...
Yunlong Liu, Matthew P. Vincenti, Hiroki Yokota