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Is Information Theory Inherently a Theory of Causation?

Machine Learning 2020-11-10 v4 Information Theory Machine Learning math.IT

Abstract

Information theory gives rise to a novel method for causal skeleton discovery by expressing associations between variables as tensors. This tensor-based approach reduces the dimensionality of the data needed to test for conditional independence, e.g., for systems comprising three variables, the causal skeleton can be determined using pair-wise determined tensors. To arrive at this result, an additional information measure, path information, is proposed.

Keywords

Cite

@article{arxiv.2010.01932,
  title  = {Is Information Theory Inherently a Theory of Causation?},
  author = {David Sigtermans},
  journal= {arXiv preprint arXiv:2010.01932},
  year   = {2020}
}

Comments

4 pages, 1 figure