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» A Toolbox of Level Set Methods
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BMCBI
2004
169views more  BMCBI 2004»
14 years 9 months ago
A power law global error model for the identification of differentially expressed genes in microarray data
Background: High-density oligonucleotide microarray technology enables the discovery of genes that are transcriptionally modulated in different biological samples due to physiolog...
Norman Pavelka, Mattia Pelizzola, Caterina Vizzard...
BMCBI
2007
194views more  BMCBI 2007»
14 years 10 months ago
Kernel-imbedded Gaussian processes for disease classification using microarray gene expression data
Background: Designing appropriate machine learning methods for identifying genes that have a significant discriminating power for disease outcomes has become more and more importa...
Xin Zhao, Leo Wang-Kit Cheung
AICT
2008
IEEE
119views Communications» more  AICT 2008»
14 years 10 months ago
Simplification of Frequency Test for Random Number Generation Based on Chi-Square
This paper presents the simplified method of random test suite based on the frequency (block) test. The test is used to check the first property of random numbers which is to have ...
Kruawan Wongpanya, Keattisak Sripimanwat, Kanok Je...
ENVSOFT
2006
125views more  ENVSOFT 2006»
14 years 10 months ago
Sensitivity analysis based on regional splits and regression trees (SARS-RT)
A global sensitivity analysis with regional properties is introduced. This method is demonstrated on two synthetic and one hydraulic example. It can be shown that an uncertainty a...
Florian Pappenberger, Ion Iorgulescu, Keith J. Bev...
SIGIR
2012
ACM
13 years 10 days ago
Top-k learning to rank: labeling, ranking and evaluation
In this paper, we propose a novel top-k learning to rank framework, which involves labeling strategy, ranking model and evaluation measure. The motivation comes from the difficul...
Shuzi Niu, Jiafeng Guo, Yanyan Lan, Xueqi Cheng