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ESANN
2007

Computational Intelligence approaches to causality detection

8 years 11 months ago
Computational Intelligence approaches to causality detection
Discovering interdependencies and causal relationships is one of the most relevant challenges raised by the information era. As more and better data become available, there is an urgent need for data-driven techniques with the capability of efficiently detecting hidden interactions. As such, this important issue is receiving increasing attention in the recent literature. The aim of the Learning Causality Special Session is to bring together theory-oriented and practitioners of this fascinating discipline. The main streams of causality detection by Computational Intelligence will be covered, namely, the probabilistic, information-theoretic, and Granger approaches.
Katerina Hlavácková-Schindler, Pablo
Added 29 Oct 2010
Updated 29 Oct 2010
Type Conference
Year 2007
Where ESANN
Authors Katerina Hlavácková-Schindler, Pablo F. Verdes
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