2 papers
cs.AI2024
Graph-based Complexity for Causal Effect by Empirical Plug-in
Rina Dechter, Annie Raichev, Alexander Ihler +1
This paper focuses on the computational complexity of computing empirical plug-in estimates for causal effect queries. Given a causal graph and observational data, any identifiable…
cs.AI2024
Estimating Causal Effects from Learned Causal Networks
Anna Raichev, Alexander Ihler, Jin Tian +1
The standard approach to answering an identifiable causal-effect query (e.g., ) when given a causal diagram and observational data is to first generate an estimand, or p…