4 papers
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…
Causal-Aware Foundation-Model for Bilevel Optimization in Discrete Choice Settings
Shivaram Subramanian, Zhengliang Xue, Markus Ettl +2
We introduce a causal aware foundation-model framework for real time optimal decision making in discrete choice environments. We propose a constrained triple-head price optimizatio…
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…
Fatigue-aware Bandits for Dependent Click Models
Junyu Cao, Wei Sun, Zuo-Jun +2
As recommender systems send a massive amount of content to keep users engaged, users may experience fatigue which is contributed by 1) an overexposure to irrelevant content, 2) bor…