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ICML
2006
IEEE
16 years 2 months ago
Efficient learning of Naive Bayes classifiers under class-conditional classification noise
We address the problem of efficiently learning Naive Bayes classifiers under classconditional classification noise (CCCN). Naive Bayes classifiers rely on the hypothesis that the ...
Christophe Nicolas Magnan, François Denis, ...
AGENTS
2001
Springer
15 years 5 months ago
Collaborative multiagent learning for classification tasks
Multiagent learning di ers from standard machine learning in that most existing learning methods assume that all knowledge is available locally in a single agent. In multiagent sy...
Pragnesh Jay Modi, Wei-Min Shen
STACS
1999
Springer
15 years 5 months ago
A Complete and Tight Average-Case Analysis of Learning Monomials
Abstract. We advocate to analyze the average complexity of learning problems. An appropriate framework for this purpose is introduced. Based on it we consider the problem of learni...
Rüdiger Reischuk, Thomas Zeugmann
JSS
2008
122views more  JSS 2008»
14 years 12 months ago
Traffic-aware stress testing of distributed real-time systems based on UML models using genetic algorithms
This report presents a model-driven, stress test methodology aimed at increasing chances of discovering faults related to network traffic in Distributed Real-Time Systems (DRTS). T...
Vahid Garousi, Lionel C. Briand, Yvan Labiche
COGSCI
2007
99views more  COGSCI 2007»
15 years 1 months ago
Language Evolution by Iterated Learning With Bayesian Agents
Languages are transmitted from person to person and generation to generation via a process of iterated learning: people learn a language from other people who once learned that la...
Thomas L. Griffiths, Michael L. Kalish