2 papers
stat.ML2026
Debiased Machine Learning for Conformal Prediction of Counterfactual Outcomes Under Runtime Confounding
Keith Barnatchez, Kevin P. Josey, Rachel C. Nethery +1
Data-driven decision making frequently relies on predicting counterfactual outcomes. In practice, researchers commonly train counterfactual prediction models on a source dataset to…
stat.ME2025
Multi-Task Learning for Sparsity Pattern Heterogeneity: Statistical and Computational Perspectives
Kayhan Behdin, Gabriel Loewinger, Kenneth T. Kishida +2
We consider a problem in Multi-Task Learning (MTL) where multiple linear models are jointly trained on a collection of datasets ("tasks"). A key novelty of our framework is that it…