SNAP repeatedly removes variables that cannot be ancestors of the targets, so targeted causal effects can be learned from a much smaller causal graph.
Local causal discovery with linear non-gaussian cyclic models
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SNAP: Sequential Non-Ancestor Pruning for Targeted Causal Effect Estimation With an Unknown Graph
SNAP repeatedly removes variables that cannot be ancestors of the targets, so targeted causal effects can be learned from a much smaller causal graph.