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Evaluating Model Robustness and Stability to Dataset Shift.

, , and . AISTATS, volume 130 of Proceedings of Machine Learning Research, page 2611-2619. PMLR, (2021)

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I-SPEC: An End-to-End Framework for Learning Transportable, Shift-Stable Models., and . CoRR, (2020)Learning Treatment-Response Models from Multivariate Longitudinal Data., , and . UAI, AUAI Press, (2017)Designing monitoring strategies for deployed machine learning algorithms: navigating performativity through a causal lens., , , , , , , , , and . CLeaR, volume 236 of Proceedings of Machine Learning Research, page 587-608. PMLR, (2024)Tutorial: Safe and Reliable Machine Learning., and . CoRR, (2019)Preventing Failures Due to Dataset Shift: Learning Predictive Models That Transport, , and . (2018)cite arxiv:1812.04597Comment: In Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics (AISTATS), 2019. Previously presented at the NeurIPS 2018 Causal Learning Workshop.Preventing Failures Due to Dataset Shift: Learning Predictive Models That Transport., , and . AISTATS, volume 89 of Proceedings of Machine Learning Research, page 3118-3127. PMLR, (2019)Counterfactual Normalization: Proactively Addressing Dataset Shift and Improving Reliability Using Causal Mechanisms., and . CoRR, (2018)A bias evaluation checklist for predictive models and its pilot application for 30-day hospital readmission models., , , , , , and . J. Am. Medical Informatics Assoc., 29 (8): 1323-1333 (2022)Counterfactual Normalization: Proactively Addressing Dataset Shift Using Causal Mechanisms., and . UAI, page 947-957. AUAI Press, (2018)Evaluating Model Robustness and Stability to Dataset Shift., , and . AISTATS, volume 130 of Proceedings of Machine Learning Research, page 2611-2619. PMLR, (2021)