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» Learning Rules from Distributed Data
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CEC
2008
IEEE
15 years 6 months ago
Distributed multi-relational data mining based on genetic algorithm
—An efficient algorithm for mining important association rule from multi-relational database using distributed mining ideas. Most existing data mining approaches look for rules i...
Wenxiang Dou, Jinglu Hu, Kotaro Hirasawa, Gengfeng...
80
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ALT
2002
Springer
15 years 8 months ago
How to Achieve Minimax Expected Kullback-Leibler Distance from an Unknown Finite Distribution
Abstract. We consider a problem that is related to the “Universal Encoding Problem” from information theory. The basic goal is to find rules that map “partial information”...
Dietrich Braess, Jürgen Forster, Tomas Sauer,...
ACL
2012
13 years 2 months ago
Joint Feature Selection in Distributed Stochastic Learning for Large-Scale Discriminative Training in SMT
With a few exceptions, discriminative training in statistical machine translation (SMT) has been content with tuning weights for large feature sets on small development data. Evid...
Patrick Simianer, Stefan Riezler, Chris Dyer
SIGIR
2008
ACM
14 years 11 months ago
Learning to rank at query-time using association rules
Some applications have to present their results in the form of ranked lists. This is the case of many information retrieval applications, in which documents must be sorted accordi...
Adriano Veloso, Humberto Mossri de Almeida, Marcos...
FUZZIEEE
2007
IEEE
15 years 6 months ago
Learning Fuzzy Linguistic Models from Low Quality Data by Genetic Algorithms
— Incremental rule base learning techniques can be used to learn models and classifiers from interval or fuzzyvalued data. These algorithms are efficient when the observation e...
Luciano Sánchez, José Otero