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BMCBI
2010
109views more  BMCBI 2010»
13 years 9 months ago
Application of machine learning methods to histone methylation ChIP-Seq data reveals H4R3me2 globally represses gene expression
Background: In the last decade, biochemical studies have revealed that epigenetic modifications including histone modifications, histone variants and DNA methylation form a comple...
Xiaojiang Xu, Stephen Hoang, Marty W. Mayo, Stefan...
JMLR
2010
152views more  JMLR 2010»
13 years 3 months ago
The SHOGUN Machine Learning Toolbox
We have developed a machine learning toolbox, called SHOGUN, which is designed for unified large-scale learning for a broad range of feature types and learning settings. It offers...
Sören Sonnenburg, Gunnar Rätsch, Sebasti...
KDD
2004
ACM
139views Data Mining» more  KDD 2004»
14 years 9 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
ICML
2009
IEEE
14 years 9 months ago
Prototype vector machine for large scale semi-supervised learning
Practical data mining rarely falls exactly into the supervised learning scenario. Rather, the growing amount of unlabeled data poses a big challenge to large-scale semi-supervised...
Kai Zhang, James T. Kwok, Bahram Parvin
ICALT
2005
IEEE
14 years 2 months ago
English Class on the Air: Mobile Language Learning with Cell Phones
Busy, active adults often do not have the time or ability to study in traditional, face-to-face classroom settings. In addition, adult learners may need access to content or exper...
Timothy G. Collins