Model Distillation for Revenue Optimization: Interpretable Personalized Pricing. - Max Biggs; Wei Sun 031; Markus Ettl (ICML, 2021)

Loss Functions for Discrete Contextual Pricing with Observational Data. - Max Biggs; Ruijiang Gao; Wei Sun 031 (CoRR, 2021)

Enhancing Counterfactual Classification via Self-Training. - Ruijiang Gao; Max Biggs; Wei Sun 031; Ligong Han (CoRR, 2021)

Enhancing Counterfactual Classification Performance via Self-Training. - Ruijiang Gao; Max Biggs; Wei Sun 031; Ligong Han (AAAI, 2022)

Convex Loss Functions for Contextual Pricing with Observational Posted-Price Data. - Max Biggs (CoRR, 2022)

Tightness of prescriptive tree-based mixed-integer optimization formulations. - Max Biggs; Georgia Perakis (CoRR, 2023)

Tight mixed-integer optimization formulations for prescriptive trees. - Max Biggs; Georgia Perakis (Mach. Learn., 2025)