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Why adaptively collected data have negative bias and how to correct for it., , , and . CoRR, (2017)SkinCon: A skin disease dataset densely annotated by domain experts for fine-grained model debugging and analysis., , , , and . CoRR, (2023)Collecting data when missingness is unknown: a method for improving model performance given under-reporting in patient populations., , , , and . CHIL, volume 209 of Proceedings of Machine Learning Research, page 229-242. PMLR, (2023)Grading of Prostate Whole-slide Images Using Weak Self-supervised Learning., , and . IEEECONF, page 1439-1443. IEEE, (2022)How Does Mixup Help With Robustness and Generalization?, , , , and . ICLR, OpenReview.net, (2021)Beta Shapley: a Unified and Noise-reduced Data Valuation Framework for Machine Learning., and . AISTATS, volume 151 of Proceedings of Machine Learning Research, page 8780-8802. PMLR, (2022)Competing AI: How does competition feedback affect machine learning?, , , and . AISTATS, volume 130 of Proceedings of Machine Learning Research, page 1693-1701. PMLR, (2021)When and How Mixup Improves Calibration., , , and . ICML, volume 162 of Proceedings of Machine Learning Research, page 26135-26160. PMLR, (2022)Estimating the unseen from multiple populations., , and . ICML, volume 70 of Proceedings of Machine Learning Research, page 2855-2863. PMLR, (2017)Talking Nonsense: Probing Large Language Models' Understanding of Adversarial Gibberish Inputs., and . CoRR, (2024)