From Statistical Transportability to Estimating the Effect of Stochastic Interventions
Authors: Juan D. Correa, Elias Bareinboim
IJCAI 2019 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We start by proving sufficient and necessary graphical conditions under which a probability distribution observed in the source domain can be extrapolated to the target one, where strictly less data is available. We develop the first sound and complete procedure for statistical transportability, which formally closes the problem introduced by PB. Further, we tackle the general challenge of identification of stochastic interventions from observational data [Sec. 4.4, Pearl, 2000]. This problem has been solved in the context of atomic interventions using Pearl s do-calculus, which lacks complete treatment in the stochastic case. We prove completeness of stochastic identification by constructing a reduction of any instance of this problem to an instance of statistical transportability, closing the problem. |
| Researcher Affiliation | Academia | Juan D. Correa and Elias Bareinboim Department of Computer Science, Purdue University, IN, USA {correagr, eb}@purdue.edu |
| Pseudocode | Yes | Algorithm 1 Identify*(C, H, T, L, Q, G); Algorithm 2 Transport*(G, G , Y, X, W) |
| Open Source Code | No | The paper does not provide any concrete access to source code, such as a repository link, an explicit code release statement, or code in supplementary materials, for the methodology described. |
| Open Datasets | No | The paper is theoretical and does not describe experiments that use a publicly available or open dataset for training purposes. |
| Dataset Splits | No | The paper is theoretical and does not describe experiments that involve dataset splits for training, validation, or testing. |
| Hardware Specification | No | The paper is theoretical and does not describe any experimental setup requiring hardware specifications. |
| Software Dependencies | No | The paper is theoretical and does not describe any experimental setup requiring specific ancillary software details with version numbers. |
| Experiment Setup | No | The paper is theoretical and does not provide specific experimental setup details such as hyperparameter values or training configurations. |