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cs.LG2025
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…
cs.LG2025
Learning Optimal Classification Trees Robust to Distribution Shifts
Nathan Justin, Sina Aghaei, Andrés Gómez +1
We consider the problem of learning classification trees that are robust to distribution shifts between training and testing/deployment data. This problem arises frequently in high…
cs.LG2025
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…