Detailed Information

Transportability from multiple environments with limited experiments

Cited 0 time in Web of Science Cited 12 time in Scopus

Bareinboim, Elias; Lee, Sanghack; Honavar, Vasant; Pearl, Judea

Issue Date
Neural information processing systems foundation
Advances in Neural Information Processing Systems
This paper considers the problem of transferring experimental findings learned from multiple heterogeneous domains to a target domain, in which only limited experiments can be performed. We reduce questions of transportability from multiple domains and with limited scope to symbolic derivations in the causal calculus, thus extending the original setting of transportability introduced in [1], which assumes only one domain with full experimental information available. We further provide different graphical and algorithmic conditions for computing the transport formula in this setting, that is, a way of fusing the observational and experimental information scattered throughout different domains to synthesize a consistent estimate of the desired effects in the target domain. We also consider the issue of minimizing the variance of the produced estimand in order to increase power.
Files in This Item:
There are no files associated with this item.
Appears in Collections:

Related Researcher

  • Graduate School of Data Science
Research Area Causal Decision Making, Causal Discovery, Causal Inference


Item View & Download Count

  • mendeley

Items in S-Space are protected by copyright, with all rights reserved, unless otherwise indicated.