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…
An Optimistic-Robust Approach for Dynamic Positioning of Omnichannel Inventories
Pavithra Harsha, Shivaram Subramanian, Ali Koc +4
We introduce a new class of data-driven and distribution-free optimistic-robust bimodal inventory optimization (BIO) strategy to effectively allocate inventory across a retail chai…