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» A statistical approach to rule learning
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BMCBI
2008
174views more  BMCBI 2008»
15 years 6 months ago
Evolutionary approaches for the reverse-engineering of gene regulatory networks: A study on a biologically realistic dataset
Background: Inferring gene regulatory networks from data requires the development of algorithms devoted to structure extraction. When only static data are available, gene interact...
Cédric Auliac, Vincent Frouin, Xavier Gidro...
ANLP
1997
86views more  ANLP 1997»
15 years 7 months ago
Nymble: a High-Performance Learning Name-finder
This paper presents a statistical, learned approach to finding names and other nonrecursive entities in text (as per the MUC-6 definition of the NE task), using a variant of the s...
Daniel M. Bikel, Scott Miller, Richard M. Schwartz...
NIPS
1998
15 years 7 months ago
Gradient Descent for General Reinforcement Learning
A simple learning rule is derived, the VAPS algorithm, which can be instantiated to generate a wide range of new reinforcementlearning algorithms. These algorithms solve a number ...
Leemon C. Baird III, Andrew W. Moore
ECAI
2000
Springer
15 years 10 months ago
Learning Classification taxonomies from a classification knowledge based system
Knowledge-based systems (KBS) are not necessarily based on well-defined ontologies. In particular it is possible to build KBS for classification problems, where there is little con...
Hendra Suryanto, Paul Compton
ISMIS
1999
Springer
15 years 10 months ago
Learning English Grapheme Segmentation Using the Iterated Version Space Algorithm
Abstract. Our unique approach for learning English grapheme segmentation (LE-GS) rules using the Iterated Version Space Algorithm (IVSA) is presented. After de ning the problem and...
Jianna Jian Zhang, Howard J. Hamilton, Nick Cercon...