33 citations · 117 across the 22 of their papers we have counts for
24 papers
Learning Risk Scores Robust to Unobserved Confounders
Ryan Edmonds, Yingxiao Ye, Sina Aghaei +3
We consider the problem of learning risk scores to prioritize individuals for scarce resources or interventions, from historical observational data affected by unobserved confoundi…
Toward AI Matching Policies in Homeless Services: A Qualitative Study with Policymakers
Caroline M. Johnston, Olga Koumoundouros, Angel Hsing-Chi Hwang +3
Artificial intelligence researchers have proposed various data-driven algorithms to improve the processes that match individuals experiencing homelessness to scarce housing resourc…
Making a Case for Research Collaboration Between Artificial Intelligence and Operations Research Experts
Radhika Kulkarni, Gianluca Brero, Yu Ding +7
In 2021, INFORMS, ACM SIGAI, and the Computing Community Consortium (CCC) hosted three workshops to explore synergies between Artificial Intelligence (AI) and Operations Research (…
Responsible Machine Learning via Mixed-Integer Optimization
Nathan Justin, Qingshi Sun, Andrés Gómez +1
In the last few decades, Machine Learning (ML) has achieved significant success across domains ranging from healthcare, sustainability, and the social sciences, to criminal justice…
Mixed-feature Logistic Regression Robust to Distribution Shifts
Qingshi Sun, Nathan Justin, Andres Gomez +1
Logistic regression models are widely used in the social and behavioral sciences and in high-stakes domains, due to their simplicity and interpretability properties. At the same ti…
Distributionally Robust Optimization with Decision-Dependent Information Discovery
Qing Jin, Angelos Georghiou, Phebe Vayanos +1
We study two-stage distributionally robust optimization (DRO) problems with decision-dependent information discovery (DDID) wherein (a portion of) the uncertain parameters are reve…