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» Two Algorithms for Inducing Causal Models from Data
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FSTTCS
1993
Springer
15 years 7 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
15 years 4 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»
14 years 10 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
15 years 9 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»
15 years 3 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,...