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  Distinguishing Between Cause and Effect via Kernel-Based Complexity Measures for Conditional Distributions

Sun, X., Janzing, D., & Schölkopf, B. (2007). Distinguishing Between Cause and Effect via Kernel-Based Complexity Measures for Conditional Distributions. In M. Verleysen (Ed.), Advances in computational intelligence and learning: 15th European Symposium on Artificial Neural Networks: ESANN 2007 (pp. 441-446). Evere, Belgium: D-Side Publications.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0013-CE19-C Version Permalink: http://hdl.handle.net/21.11116/0000-0003-E32B-D
Genre: Conference Paper

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ESANN-2007-Sun.pdf (Any fulltext), 683KB
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 Creators:
Sun, X1, 2, Author              
Janzing, D, Author              
Schölkopf, B1, 2, Author              
Affiliations:
1Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795              
2biological cy, ou_persistent22              

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 Abstract: We propose a method to evaluate the complexity of probability measures from data that is based on a reproducing kernel Hilbert space seminorm of the logarithm of conditional probability densities. The motivation is to provide a tool for a causal inference method which assumes that conditional probabilities for effects given their causes are typically simpler and smoother than vice-versa. We present experiments with toy data where the quantitative results are consistent with our intuitive understanding of complexity and smoothness. Also in some examples with real-world data the probability measure corresponding to the true causal direction turned out to be less complex than those of the reversed order.

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Language(s):
 Dates: 2007-04
 Publication Status: Published in print
 Pages: -
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 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: 4454
 Degree: -

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Title: 15th European Symposium on Artificial Neural Networks (ESANN 2007)
Place of Event: Brugge, Belgium
Start-/End Date: 2007-04-25 - 2007-04-27

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Title: Advances in computational intelligence and learning: 15th European Symposium on Artificial Neural Networks: ESANN 2007
Source Genre: Proceedings
 Creator(s):
Verleysen, M, Editor
Affiliations:
-
Publ. Info: Evere, Belgium : D-Side Publications
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 441 - 446 Identifier: ISBN: 2-930307-07-2