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Mixed Differential Privacy in Computer Vision., , , , , and . CVPR, page 8366-8376. IEEE, (2022)Multicalibration as Boosting for Regression., , , , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 11459-11492. PMLR, (2023)A Bound on the Error of Cross Validation Using the Approximation and Estimation Rates, with Consequences for the Training-Test Split. Advances in Neural Information Processing Systems, 8, page 183--189. (1996)Regret to the Best vs. Regret to the Average, , , and . Learning Theory, page 233--247. Berlin, Heidelberg, Springer Berlin Heidelberg, (2007)Cryptographic limitations on learning Boolean formulae and finite automata, and . Journal of the ACM, 41 (1): 67--95 (1994)Convergent Algorithms for (Relaxed) Minimax Fairness., , , , and . CoRR, (2020)Improved Differentially Private Regression via Gradient Boosting., , , , , , , and . SaTML, page 33-56. IEEE, (2024)Near-optimal reinforcement learning in polynomial time, and . Proc. 15th International Conf. on Machine Learning, page 260--268. Morgan Kaufmann, San Francisco, CA, (1998)An Experimental Study of the Coloring Problem on Human Subject Networks, , and . (August 2006)Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness, , , and . (2017)cite arxiv:1711.05144Comment: Added new experimental results and a slightly modified fairness definition.