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115
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PKDD
2010
Springer
148views Data Mining» more  PKDD 2010»
14 years 10 months ago
Exploiting Causal Independence in Markov Logic Networks: Combining Undirected and Directed Models
Abstract. A new method is proposed for compiling causal independencies into Markov logic networks (MLNs). An MLN can be viewed as compactly representing a factorization of a joint ...
Sriraam Natarajan, Tushar Khot, Daniel Lowd, Prasa...
83
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CONNECTION
2006
101views more  CONNECTION 2006»
14 years 11 months ago
Learning acceptable windows of contingency
By learning a range of possible times over which the effect of an action can take place, a robot can reason more effectively about causal and contingent relationships in the world...
Kevin Gold, Brian Scassellati
ESANN
2007
15 years 1 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 u...
Katerina Hlavácková-Schindler, Pablo...
KDD
2009
ACM
230views Data Mining» more  KDD 2009»
15 years 4 months ago
Grouped graphical Granger modeling methods for temporal causal modeling
We develop and evaluate an approach to causal modeling based on time series data, collectively referred to as“grouped graphical Granger modeling methods.” Graphical Granger mo...
Aurelie C. Lozano, Naoki Abe, Yan Liu, Saharon Ros...
COGSCI
2004
120views more  COGSCI 2004»
14 years 11 months ago
Children's causal inferences from indirect evidence: Backwards blocking and Bayesian reasoning in preschoolers
Previous research suggests that children can infer causal relations from patterns of events. However, what appear to be cases of causal inference may simply reduce to children rec...
David M. Sobel, Joshua B. Tenenbaum, Alison Gopnik