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          Institute: MPI für Intelligente Systeme (ehemals Max-Planck-Institut für Metallforschung)     Collection: Abt. Schölkopf (Empirical Inference)     Display Documents

ID: 596824.0, MPI für Intelligente Systeme (ehemals Max-Planck-Institut für Metallforschung) / Abt. Schölkopf (Empirical Inference)
Testing whether linear equations are causal: A free probability theory approach
Authors:Zscheischler, J.; Janzing, D.; Zhang, K.
Publisher:AUAI Press
Place of Publication:Corvallis, OR, USA
Date of Publication (YYYY-MM-DD):2011-07-01
Title of Proceedings:27th Conference on Uncertainty in Artificial Intelligence (UAI 2011)
Start Page:839
End Page:847
Physical Description:8
Place of Conference/Meeting:Barcelona, Spain
Review Status:not specified
Audience:Not Specified
Intended Educational Use:No
Abstract / Description:We propose a method that infers whether linear relations between two high-dimensional variables X and Y are due to a causal influence from X to Y or from Y to X. The earlier proposed so-called Trace Method is extended to the regime where the dimension of the observed variables exceeds the sample size. Based on previous work, we postulate
conditions that characterize a causal relation between X and Y . Moreover, we describe a statistical test and argue that both causal directions are typically rejected if there is a common cause. A full theoretical analysis is
presented for the deterministic case but our approach seems to be valid for the noisy case, too, for which we additionally present an approach based on a sparsity constraint. The discussed method yields promising results for both simulated and real world data.
External Publication Status:published
Document Type:Conference-Paper
Communicated by:Heide Klooz
Affiliations:MPI für Intelligente Systeme/Abt. Schölkopf
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