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Towards Safe and Aligned Large Language Models for Medicine., , , и . CoRR, (2024)What will it take to generate fairness-preserving explanations?, , , и . CoRR, (2021)Learning Cost-Effective and Interpretable Treatment Regimes., и . AISTATS, том 54 из Proceedings of Machine Learning Research, стр. 166-175. PMLR, (2017)Efficient Training of Low-Curvature Neural Networks., , , и . NeurIPS, (2022)OpenXAI: Towards a Transparent Evaluation of Model Explanations., , , , , , , и . NeurIPS, (2022)Learning Models for Actionable Recourse., , и . NeurIPS, стр. 18734-18746. (2021)Incorporating Interpretable Output Constraints in Bayesian Neural Networks., , , , и . NeurIPS, (2020)Fair Influence Maximization: a Welfare Optimization Approach., , , , , , , и . AAAI, стр. 11630-11638. AAAI Press, (2021)On the Impact of Algorithmic Recourse on Social Segregation., и . ICML, том 202 из Proceedings of Machine Learning Research, стр. 10727-10743. PMLR, (2023)Human-centric machine learning: enabling machine learning for high-stakes decision-making.. Stanford University, USA, (2018)