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» Feature selection in scientific applications
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HPDC
2010
IEEE
13 years 11 months ago
A data transfer framework for large-scale science experiments
Modern scientific experiments can generate hundreds of gigabytes to terabytes or even petabytes of data that may furthermore be maintained in large numbers of relatively small fil...
Wantao Liu, Brian Tieman, Rajkumar Kettimuthu, Ian...
CORR
2006
Springer
98views Education» more  CORR 2006»
13 years 10 months ago
Enabling user-driven Checkpointing strategies in Reverse-mode Automatic Differentiation
This paper presents a new functionality of the Automatic Differentiation (AD) Tool tapenade. tapenade generates adjoint codes which are widely used for optimization or inverse prob...
Laurent Hascoët, Mauricio Araya-Polo
NLDB
2010
Springer
13 years 8 months ago
Extracting Meronymy Relationships from Domain-Specific, Textual Corporate Databases
Abstract. Various techniques for learning meronymy relationships from opendomain corpora exist. However, extracting meronymy relationships from domain-specific, textual corporate d...
Ashwin Ittoo, Gosse Bouma, Laura Maruster, Hans Wo...
BMCBI
2008
83views more  BMCBI 2008»
13 years 10 months ago
Models of deletion for visualizing bacterial variation: an application to tuberculosis spoligotypes
Background: Molecular typing methods are commonly used to study genetic relationships among bacterial isolates. Many of these methods have become standardized and produce portable...
Josephine F. Reyes, Andrew R. Francis, Mark M. Tan...
RSFDGRC
2005
Springer
190views Data Mining» more  RSFDGRC 2005»
14 years 3 months ago
Finding Rough Set Reducts with SAT
Abstract. Feature selection refers to the problem of selecting those input features that are most predictive of a given outcome; a problem encountered in many areas such as machine...
Richard Jensen, Qiang Shen, Andrew Tuson