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  Identifying confounders using additive noise models

Janzing, D., Peters, J., Mooij, J., & Schölkopf, B. (2009). Identifying confounders using additive noise models. In N. Bilmes, A. Ng, & D. McAllester (Eds.), 25th Conference on Uncertainty in Artificial Intelligence (UAI 2009) (pp. 249-257). Corvallis, OR, USA: AUAI Press.

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Item Permalink: https://hdl.handle.net/11858/00-001M-0000-0013-C481-3 Version Permalink: https://hdl.handle.net/21.11116/0000-0002-F8EB-E
Genre: Conference Paper

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 Creators:
Janzing, D1, 2, Author           
Peters, J1, 2, Author           
Mooij, JM1, 2, Author           
Schölkopf, B1, 2, Author           
Affiliations:
1Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

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 Abstract: We propose a method for inferring the existence of a latent common cause ("confounder") of two observed random variables.
The method assumes that the two effects of
the confounder are (possibly nonlinear) functions
of the confounder plus independent, additive
noise. We discuss under which conditions
the model is identifiable (up to an arbitrary
reparameterization of the confounder)
from the joint distribution of the effects. We
state and prove a theoretical result that provides
evidence for the conjecture that the
model is generically identifiable under suitable
technical conditions. In addition, we
propose a practical method to estimate the
confounder from a finite i.i.d. sample of the
effects and illustrate that the method works
well on both simulated and real-world data.

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 Dates: 2009-06
 Publication Status: Issued
 Pages: -
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 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: 5903
 Degree: -

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Title: 25th Conference on Uncertainty in Artificial Intelligence (UAI 2009)
Place of Event: Montréal, Canada
Start-/End Date: 2009-06-18 - 2009-06-21

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Title: 25th Conference on Uncertainty in Artificial Intelligence (UAI 2009)
Source Genre: Proceedings
 Creator(s):
Bilmes, NJ, Editor
Ng, AY, Editor
McAllester, DA, Editor
Affiliations:
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Publ. Info: Corvallis, OR, USA : AUAI Press
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 249 - 257 Identifier: ISBN: 978-0-9749039-5-8