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Exploring Counterfactual Explanations Through the Lens of Adversarial Examples: A Theoretical and Empirical Analysis.

, , , , and . AISTATS, volume 151 of Proceedings of Machine Learning Research, page 4574-4594. PMLR, (2022)

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Confounding Feature Acquisition for Causal Effect Estimation., , , and . ML4H@NeurIPS, volume 136 of Proceedings of Machine Learning Research, page 379-396. PMLR, (2020)Towards Robust and Reliable Algorithmic Recourse., , and . NeurIPS, page 16926-16937. (2021)What's fair is... fair? Presenting JustEFAB, an ethical framework for operationalizing medical ethics and social justice in the integration of clinical machine learning: JustEFAB., , , , , , , , , and 5 other author(s). FAccT, page 1505-1519. ACM, (2023)Can You Fake It Until You Make It?: Impacts of Differentially Private Synthetic Data on Downstream Classification Fairness., , , , and . FAccT, page 149-160. ACM, (2021)Exploring Counterfactual Explanations Through the Lens of Adversarial Examples: A Theoretical and Empirical Analysis., , , , and . AISTATS, volume 151 of Proceedings of Machine Learning Research, page 4574-4594. PMLR, (2022)"Why did the Model Fail?": Attributing Model Performance Changes to Distribution Shifts., , , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 41550-41578. PMLR, (2023)What went wrong and when? Instance-wise Feature Importance for Time-series Models., , , and . CoRR, (2020)What Clinicians Want: Contextualizing Explainable Machine Learning for Clinical End Use., , , and . MLHC, volume 106 of Proceedings of Machine Learning Research, page 359-380. PMLR, (2019)Towards Safe Policy Learning under Partial Identifiability: A Causal Approach., , and . AAAI, page 13004-13012. AAAI Press, (2024)Simultaneous Prognosis of Multiple Chronic Conditions from Heterogeneous EHR Data., , and . ICHI, page 497. IEEE Computer Society, (2015)