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ICML
2006
IEEE
16 years 7 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, ...
FLAIRS
2004
15 years 7 months ago
Using Previous Experience for Learning Planning Control Knowledge
Machine learning (ML) is often used to obtain control knowledge to improve planning efficiency. Usually, ML techniques are used in isolation from experience that could be obtained...
Susana Fernández, Ricardo Aler, Daniel Borr...
PTS
2007
97views Hardware» more  PTS 2007»
15 years 8 months ago
Learning and Integration of Parameterized Components Through Testing
Abstract. We investigate the use of parameterized state machine models to drive integration testing, in the case where the models of components are not available beforehand. Theref...
Muzammil Shahbaz, Keqin Li 0002, Roland Groz
COLT
2005
Springer
16 years 22 hour ago
Separating Models of Learning from Correlated and Uncorrelated Data
We consider a natural framework of learning from correlated data, in which successive examples used for learning are generated according to a random walk over the space of possibl...
Ariel Elbaz, Homin K. Lee, Rocco A. Servedio, Andr...
IJCAI
2003
15 years 7 months ago
Statistics Gathering for Learning from Distributed, Heterogeneous and Autonomous Data Sources
With the growing use of distributed information networks, there is an increasing need for algorithmic and system solutions for data-driven knowledge acquisition using distributed,...
Doina Caragea, Jaime Reinoso, Adrian Silvescu, Vas...