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FOCS
2000
IEEE
14 years 6 days ago
Extracting Randomness from Samplable Distributions
Randomness extractors convert weak sources of randomness into an almost uniform distribution; the conversion uses a small amount of pure randomness. In algorithmic applications, t...
Luca Trevisan, Salil P. Vadhan
JCB
2008
94views more  JCB 2008»
13 years 7 months ago
Prioritize and Select SNPs for Association Studies with Multi-Stage Designs
Large-scale whole genome association studies are increasingly common, due in large part to recent advances in genotyping technology. With this change in paradigm for genetic studi...
Jing Li
BMCBI
2006
126views more  BMCBI 2006»
13 years 7 months ago
Differential prioritization between relevance and redundancy in correlation-based feature selection techniques for multiclass ge
Background: Due to the large number of genes in a typical microarray dataset, feature selection looks set to play an important role in reducing noise and computational cost in gen...
Chia Huey Ooi, Madhu Chetty, Shyh Wei Teng
CORR
2000
Springer
91views Education» more  CORR 2000»
13 years 7 months ago
Algorithmic Theories of Everything
The probability distribution P from which the history of our universe is sampled represents a theory of everything or TOE. We assume P is formally describable. Since most (uncount...
Jürgen Schmidhuber
ICIP
2004
IEEE
14 years 9 months ago
New features for affine-invariant shape classification
An object seen from different viewpoints results in differently deformed images. Affine-invariant shape classification must classify correctly the object, disregarding its viewpoi...
Carlos Ramon Pantaleon Dionisio, Hae Yong Kim