4 papers
"It Was a Magical Box": Understanding Practitioner Workflows and Needs in Optimization
Connor Lawless, Jakob Schoeffer, Madeleine Udell
Optimization underpins decision-making in domains from healthcare to logistics, yet for many practitioners it remains a "magical box": powerful but opaque, difficult to use, and re…
Understanding Fixed Predictions via Confined Regions
Connor Lawless, Tsui-Wei Weng, Berk Ustun +1
Machine learning models can assign fixed predictions that preclude individuals from changing their outcome. Existing approaches to audit fixed predictions do so on a pointwise basi…
EquivaMap: Leveraging LLMs for Automatic Equivalence Checking of Optimization Formulations
Haotian Zhai, Connor Lawless, Ellen Vitercik +1
A fundamental problem in combinatorial optimization is identifying equivalent formulations. Despite the growing need for automated equivalence checks -- driven, for example, by opt…
LLMs for Cold-Start Cutting Plane Separator Configuration
Connor Lawless, Yingxi Li, Anders Wikum +2
Mixed integer linear programming (MILP) solvers expose hundreds of parameters that have an outsized impact on performance but are difficult to configure for all but expert users. E…