2 papers
cs.LG2026
Counterfactual Optimal Action Trees (COAT): Interpretable Prescriptive Policies from Observational Data
Youssef Drissi, Markus Ettl, Shivaram Subramanian +2
We introduce COAT (Counterfactual Optimal Action Tree), a framework for learning interpretable prescriptive policies from observational data. COAT combines counterfactual outcome e…
cs.LG2024
PresAIse, A Prescriptive AI Solution for Enterprises
Wei Sun, Scott McFaddin, Linh Ha Tran +6
Prescriptive AI represents a transformative shift in decision-making, offering causal insights and actionable recommendations. Despite its huge potential, enterprise adoption often…