2022
Efficient interventional distribution learning in the PAC framework
AISTATS 2022poster
We consider the problem of efficiently inferring interventional distributions in a causal Bayesian network from a finite number of observations. Let P be a causal model on a set V of observable variables on a given causal graph G. For sets $X,Y \subseteq V$, and setting x to $X$, $P_x(Y)$ denotes th…