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PKDD
2010
Springer
148views Data Mining» more  PKDD 2010»
10 years 12 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...
ADVCS
2008
83views more  ADVCS 2008»
11 years 1 days ago
Information Flows in Causal Networks
We introduce a notion of causal independence based on virtual intervention, which is a fundamental concept of the theory of causal networks. Causal independence allows for de ning ...
Nihat Ay, Daniel Polani
AI
2005
Springer
11 years 1 months ago
Bayesian network modelling through qualitative patterns
In designing a Bayesian network for an actual problem, developers need to bridge the gap between ematical abstractions offered by the Bayesian-network formalism and the features o...
Peter J. F. Lucas
UAI
1994
11 years 2 months ago
A New Look at Causal Independence
Heckerman (1993) defined causal independence in terms of a set of temporal conditional independence statements. These statements formalized certain types of causal interaction whe...
David Heckerman, John S. Breese
ECML
2006
Springer
11 years 5 months ago
EM Algorithm for Symmetric Causal Independence Models
Causal independence modelling is a well-known method both for reducing the size of probability tables and for explaining the underlying mechanisms in Bayesian networks. In this pap...
Rasa Jurgelenaite, Tom Heskes
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