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KDD
2004
ACM
139views Data Mining» more  KDD 2004»
14 years 10 months ago
Learning a complex metabolomic dataset using random forests and support vector machines
Metabolomics is the omics science of biochemistry. The associated data include the quantitative measurements of all small molecule metabolites in a biological sample. These datase...
Young Truong, Xiaodong Lin, Chris Beecher
ISPASS
2009
IEEE
14 years 4 months ago
Machine learning based online performance prediction for runtime parallelization and task scheduling
—With the emerging many-core paradigm, parallel programming must extend beyond its traditional realm of scientific applications. Converting existing sequential applications as w...
Jiangtian Li, Xiaosong Ma, Karan Singh, Martin Sch...
BMCBI
2010
176views more  BMCBI 2010»
13 years 10 months ago
TargetSpy: a supervised machine learning approach for microRNA target prediction
Background: Virtually all currently available microRNA target site prediction algorithms require the presence of a (conserved) seed match to the 5' end of the microRNA. Recen...
Martin Sturm, Michael Hackenberg, David Langenberg...
KDD
2004
ACM
139views Data Mining» more  KDD 2004»
14 years 10 months ago
Machine learning for online query relaxation
In this paper we provide a fast, data-driven solution to the failing query problem: given a query that returns an empty answer, how can one relax the query's constraints so t...
Ion Muslea
JCST
2006
128views more  JCST 2006»
13 years 10 months ago
Multi-Instance Learning from Supervised View
Abstract In multi-instance learning, the training set comprises labeled bags that are composed of unlabeled instances, and the task is to predict the labels of unseen bags. This pa...
Zhi-Hua Zhou