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» Learning to Identify Unexpected Instances in the Test Set
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BMCBI
2006
144views more  BMCBI 2006»
15 years 6 months ago
More robust detection of motifs in coexpressed genes by using phylogenetic information
Background: Several motif detection algorithms have been developed to discover overrepresented motifs in sets of coexpressed genes. However, in a noisy gene list, the number of ge...
Pieter Monsieurs, Gert Thijs, Abeer A. Fadda, Sigr...
DATE
2008
IEEE
122views Hardware» more  DATE 2008»
16 years 1 months ago
Simulation-Directed Invariant Mining for Software Verification
With the advance of SAT solvers, transforming a software program to a propositional formula has generated much interest for bounded model checking of software in recent years. How...
Xueqi Cheng, Michael S. Hsiao
PPSN
2004
Springer
16 years 2 days ago
The Application of Bayesian Optimization and Classifier Systems in Nurse Scheduling
Two ideas taken from Bayesian optimization and classifier systems are presented for personnel scheduling based on choosing a suitable scheduling rule from a set for each person’s...
Jingpeng Li, Uwe Aickelin
CCS
2009
ACM
16 years 1 months ago
Learning your identity and disease from research papers: information leaks in genome wide association study
Genome-wide association studies (GWAS) aim at discovering the association between genetic variations, particularly single-nucleotide polymorphism (SNP), and common diseases, which...
Rui Wang, Yong Fuga Li, XiaoFeng Wang, Haixu Tang,...
FLAIRS
2010
15 years 9 months ago
Visual Object Detection using Frequent Pattern Mining
Object search in a visual scene is a highly challenging and computationally intensive task. Most of the current object detection techniques extract features from images for classi...
Yousuf Aboobaker Sait, Balaraman Ravindran