Repository logo

Infoscience

  • English
  • French
Log In
Logo EPFL, École polytechnique fédérale de Lausanne

Infoscience

  • English
  • French
Log In
  1. Home
  2. Academic and Research Output
  3. Conferences, Workshops, Symposiums, and Seminars
  4. s-ID: Causal Effect Identification in a Sub-Population
 
conference paper

s-ID: Causal Effect Identification in a Sub-Population

Abouei, Amir Mohammad  
•
Mokhtarian, Ehsan  
•
Kiyavash, Negar  
Wooldridge, Michael
•
Dy, Jennifer
Show more
March 25, 2024
38 AAAI Conference on Artificial Intelligence

Causal inference in a sub-population involves identifying the causal effect of an intervention on a specific subgroup, which is distinguished from the whole population through the influence of systematic biases in the sampling process. However, ignoring the subtleties introduced by sub-populations can either lead to erroneous inference or limit the applicability of existing methods. We introduce and advocate for a causal inference problem in sub-populations (henceforth called S-ID), in which we merely have access to observational data of the targeted sub-population (as opposed to the entire population). Existing inference problems in sub-populations operate on the premise that the given data distributions originate from the entire population, thus, cannot tackle the S-ID problem. To address this gap, we provide necessary and sufficient conditions that must hold in the causal graph for a causal effect in a sub-population to be identifiable from the observational distribution of that sub-population. Given these conditions, we present a sound and complete algorithm for the S-ID problem.

  • Details
  • Metrics
Type
conference paper
DOI
10.1609/aaai.v38i18.30011
Scopus ID

2-s2.0-85189532572

Author(s)
Abouei, Amir Mohammad  
•
Mokhtarian, Ehsan  
•
Kiyavash, Negar  
Editors
Wooldridge, Michael
•
Dy, Jennifer
•
Natarajan, Sriraam
Date Issued

2024-03-25

Publisher

Association for the Advancement of Artificial Intelligence

Series title/Series vol.

Proceedings of the AAAI Conference on Artificial Intelligence; 38

ISSN (of the series)

2374-3468

2159-5399

Issue

18

Start page

20302

End page

20310

Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
BAN  
Event nameEvent acronymEvent placeEvent date
38 AAAI Conference on Artificial Intelligence

Vancouver, Canada

2024-02-20 - 2024-02-27

FunderFunding(s)Grant NumberGrant URL

SNF

200021 204355 /1,51NF40 180545

Available on Infoscience
January 26, 2025
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/245196
Logo EPFL, École polytechnique fédérale de Lausanne
  • Contact
  • infoscience@epfl.ch

  • Follow us on Facebook
  • Follow us on Instagram
  • Follow us on LinkedIn
  • Follow us on X
  • Follow us on Youtube
AccessibilityLegal noticePrivacy policyCookie settingsEnd User AgreementGet helpFeedback

Infoscience is a service managed and provided by the Library and IT Services of EPFL. © EPFL, tous droits réservés