Causal Inference, Machine Learning, Editors Pick, Bcn Causal Algo, Thoughts And Theory.
parameter of interest θ₀, in the presence of the (potentially high dimensional) nuisance parameter η₀=(g₀, m₀). In this context, nuisance means that we do not directly care about the correctness of our estimate of η₀, as far as we get a good (root n-consistent) estimator of θ₀. But why are we