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» Two Algorithms for Inducing Causal Models from Data
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FSTTCS
1993
Springer
13 years 11 months ago
Induce-Statements and Induce-Expressions: Constructs for Inductive Programming
A for-loop is somewhat similar to an inductive argument. Just as the truth of a proposition P(n + 1) depends on the truth of P(n), the correctness of iteration n+1 of a for-loop de...
Theodore S. Norvell
UAI
2008
13 years 8 months ago
Discovering Cyclic Causal Models by Independent Components Analysis
We generalize Shimizu et al's (2006) ICA-based approach for discovering linear non-Gaussian acyclic (LiNGAM) Structural Equation Models (SEMs) from causally sufficient, conti...
Gustavo Lacerda, Peter Spirtes, Joseph Ramsey, Pat...
JMLR
2010
134views more  JMLR 2010»
13 years 2 months ago
Bayesian Algorithms for Causal Data Mining
We present two Bayesian algorithms CD-B and CD-H for discovering unconfounded cause and effect relationships from observational data without assuming causal sufficiency which prec...
Subramani Mani, Constantin F. Aliferis, Alexander ...
LICS
2009
IEEE
14 years 2 months ago
The Structure of First-Order Causality
Game semantics describe the interactive behavior of proofs by interpreting formulas as games on which proofs induce strategies. Such a semantics is introduced here for capturing d...
Samuel Mimram
IJAR
2008
92views more  IJAR 2008»
13 years 7 months ago
Predicting causality ascriptions from background knowledge: model and experimental validation
A model is defined that predicts an agent's ascriptions of causality (and related notions of facilitation and justification) between two events in a chain, based on backgroun...
Jean-François Bonnefon, Rui Da Silva Neves,...