1 citations · 1 across the 4 of their papers we have counts for
Showing cs.LGShow all
2 papers · 1 filter
cs.LG2023★ 1 cited
Transparency challenges in policy evaluation with causal machine learning -- improving usability and accountability
Patrick Rehill, Nicholas Biddle
Causal machine learning tools are beginning to see use in real-world policy evaluation tasks to flexibly estimate treatment effects. One issue with these methods is that the machin…
cs.LG2022
Policy learning for many outcomes of interest: Combining optimal policy trees with multi-objective Bayesian optimisation
Patrick Rehill, Nicholas Biddle
Methods for learning optimal policies use causal machine learning models to create human-interpretable rules for making choices around the allocation of different policy interventi…