Fair Decision Rules for Binary Classification. - Connor Lawless; Oktay Günlük (CoRR, 2021)

Interpretable Clustering via Multi-Polytope Machines. - Connor Lawless; Jayant Kalagnanam; Lam M. Nguyen; Dzung T. Phan; Chandra Reddy (AAAI, 2022)

A Note on Task-Aware Loss via Reweighing Prediction Loss by Decision-Regret. - Connor Lawless; Angela Zhou (CoRR, 2022)

Cluster Explanation via Polyhedral Descriptions. - Connor Lawless; Oktay Günlük (ICML, 2023)

Interpretable and Fair Boolean Rule Sets via Column Generation. - Connor Lawless; Sanjeeb Dash; Oktay Günlük; Dennis Wei (J. Mach. Learn. Res., 2023)

Fair Minimum Representation Clustering. - Connor Lawless; Oktay Günlük (CPAIOR (2), 2024)

Fair Minimum Representation Clustering via Integer Programming. - Connor Lawless; Oktay Günlük (CoRR, 2024)

"I Want It That Way": Enabling Interactive Decision Support Using Large Language Models and Constraint Programming. - Connor Lawless; Jakob Schoeffer; Lindy Le; Kael Rowan; Shilad Sen; Cristina St. Hill; Jina Suh; Bahareh Sarrafzadeh (ACM Trans. Interact. Intell. Syst., 2024)

LLMs for Cold-Start Cutting Plane Separator Configuration. - Connor Lawless; Yingxi Li; Anders Wikum; Madeleine Udell; Ellen Vitercik (CPAIOR (2), 2025)

EquivaMap: Leveraging LLMs for Automatic Equivalence Checking of Optimization Formulations. - Haotian Zhai; Connor Lawless; Ellen Vitercik; Liu Leqi (CoRR, 2025)

Understanding Fixed Predictions via Confined Regions. - Connor Lawless; Tsui-Wei Weng; Berk Ustun; Madeleine Udell (CoRR, 2025)