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07/28/2023
ODTlearn: A Package for Learning Optimal Decision Trees for Prediction and Prescription
ODTLearn is an open-source Python package that provides methods for lear...
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06/06/2023
Deploying a Robust Active Preference Elicitation Algorithm: Experiment Design, Interface, and Evaluation for COVID-19 Patient Prioritization
Preference elicitation leverages AI or optimization to learn stakeholder...
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12/04/2022
Fairness in Contextual Resource Allocation Systems: Metrics and Incompatibility Results
We study critical systems that allocate scarce resources to satisfy basi...
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01/25/2022
Learning Resource Allocation Policies from Observational Data with an Application to Homeless Services Delivery
We study the problem of learning, from observational data, fair and inte...
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01/24/2022
Learning Optimal Fair Classification Trees
The increasing use of machine learning in high-stakes domains – where pe...
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08/31/2021
Learning Optimal Prescriptive Trees from Observational Data
We consider the problem of learning an optimal prescriptive tree (i.e., ...
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03/29/2021
Strong Optimal Classification Trees
Decision trees are among the most popular machine learning models and ar...
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06/14/2020
Fair Influence Maximization: A Welfare Optimization Approach
Several social interventions (e.g., suicide and HIV prevention) leverage...
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03/04/2020
Active Preference Elicitation via Adjustable Robust Optimization
We consider the problem faced by a recommender system which seeks to off...
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02/21/2020
Learning Optimal Classification Trees: Strong Max-Flow Formulations
We consider the problem of learning optimal binary classification trees....
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03/25/2019