Interventional dependency graphs: An approach for discovering influence structure

Jalal Etesami, Negar Kiyavash

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we introduce a new type of graphical model, interventional dependency graphs, to encode interactions among processes. These type of graphical models are defined using a measure that captures the influence relationships based on the principle of intervention. Principle of intervention discovers an influence relationship by making assignment to certain variables while fixing other variables to see how these changes influence statistics of variables of interest. Furthermore, we derive some properties of the dynamics that can be inferred from these graphs and establish the relationship between this new graphical model and the directed information graphs used for causal inference.

Original languageEnglish (US)
Title of host publicationProceedings - ISIT 2016; 2016 IEEE International Symposium on Information Theory
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1158-1162
Number of pages5
ISBN (Electronic)9781509018062
DOIs
StatePublished - Aug 10 2016
Event2016 IEEE International Symposium on Information Theory, ISIT 2016 - Barcelona, Spain
Duration: Jul 10 2016Jul 15 2016

Publication series

NameIEEE International Symposium on Information Theory - Proceedings
Volume2016-August
ISSN (Print)2157-8095

Other

Other2016 IEEE International Symposium on Information Theory, ISIT 2016
Country/TerritorySpain
CityBarcelona
Period7/10/167/15/16

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Information Systems
  • Modeling and Simulation
  • Applied Mathematics

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