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125
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SIGIR
2011
ACM
14 years 6 months ago
Parallel learning to rank for information retrieval
Learning to rank represents a category of effective ranking methods for information retrieval. While the primary concern of existing research has been accuracy, learning efficien...
Shuaiqiang Wang, Byron J. Gao, Ke Wang, Hady Wiraw...
181
Voted
ICSE
2012
IEEE-ACM
13 years 6 months ago
Recovering traceability links between an API and its learning resources
—Large frameworks and libraries require extensive developer learning resources, such as documentation and mailing lists, to be useful. Maintaining these learning resources is cha...
Barthélémy Dagenais, Martin P. Robil...
156
Voted
BMCBI
2011
14 years 10 months ago
Learning genetic epistasis using Bayesian network scoring criteria
Background: Gene-gene epistatic interactions likely play an important role in the genetic basis of many common diseases. Recently, machine-learning and data mining methods have be...
Xia Jiang, Richard E. Neapolitan, M. Michael Barma...
129
Voted
JAIR
2010
131views more  JAIR 2010»
15 years 2 months ago
Automatic Induction of Bellman-Error Features for Probabilistic Planning
Domain-specific features are important in representing problem structure throughout machine learning and decision-theoretic planning. In planning, once state features are provide...
Jia-Hong Wu, Robert Givan
139
Voted
PPSN
2010
Springer
15 years 2 months ago
Indirect Encoding of Neural Networks for Scalable Go
Abstract. The game of Go has attracted much attention from the artificial intelligence community. A key feature of Go is that humans begin to learn on a small board, and then incr...
Jason Gauci, Kenneth O. Stanley