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Comparing Population Means Under Local Differential Privacy: With Significance and Power., , , and . AAAI, page 26-33. AAAI Press, (2018)GAMformer: In-Context Learning for Generalized Additive Models., , , , , , and . CoRR, (2024)Can Generalist Foundation Models Outcompete Special-Purpose Tuning? Case Study in Medicine., , , , , , , , , and 8 other author(s). CoRR, (2023)Using Explainable Boosting Machines (EBMs) to Detect Common Flaws in Data., , , , , and . PKDD/ECML Workshops (1), volume 1524 of Communications in Computer and Information Science, page 534-551. Springer, (2021)Steering Language Model Refusal with Sparse Autoencoders., , , , , , , , and . CoRR, (2024)Using Interpretable Machine Learning to Predict Maternal and Fetal Outcomes., , , , , , , and . CoRR, (2022)Accuracy, Interpretability, and Differential Privacy via Explainable Boosting., , , , and . ICML, volume 139 of Proceedings of Machine Learning Research, page 8227-8237. PMLR, (2021)Primo: Practical Learning-Augmented Systems with Interpretable Models., , , , and . USENIX ATC, page 519-538. USENIX Association, (2022)Differentially Private Synthetic Data via Foundation Model APIs 2: Text., , , , , , , , , and 2 other author(s). ICML, OpenReview.net, (2024)From Medprompt to o1: Exploration of Run-Time Strategies for Medical Challenge Problems and Beyond., , , , , , and . CoRR, (2024)