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Locally Private Hypothesis Selection.

, , , , , and . COLT, volume 125 of Proceedings of Machine Learning Research, page 1785-1816. PMLR, (2020)

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Differentially Private Objective Perturbation: Beyond Smoothness and Convexity., , , and . CoRR, (2019)Approximately Stable, School Optimal, and Student-Truthful Many-to-One Matchings (via Differential Privacy)., , , and . CoRR, (2014)Locally Private Hypothesis Selection., , , , , and . COLT, volume 125 of Proceedings of Machine Learning Research, page 1785-1816. PMLR, (2020)Locally Private Bayesian Inference for Count Models., , , , and . ICML, volume 97 of Proceedings of Machine Learning Research, page 5638-5648. PMLR, (2019)Fair Regression: Quantitative Definitions and Reduction-Based Algorithms., , and . ICML, volume 97 of Proceedings of Machine Learning Research, page 120-129. PMLR, (2019)Bayesian Exploration: Incentivizing Exploration in Bayesian Games., , , and . Oper. Res., 70 (2): 1105-1127 (2022)The Externalities of Exploration and How Data Diversity Helps Exploitation., , , and . COLT, volume 75 of Proceedings of Machine Learning Research, page 1724-1738. PMLR, (2018)Structured Linear Contextual Bandits: A Sharp and Geometric Smoothed Analysis., , and . ICML, volume 119 of Proceedings of Machine Learning Research, page 9026-9035. PMLR, (2020)Inverse Reinforcement Learning without Reinforcement Learning., , , , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 33299-33318. PMLR, (2023)Approximately Stable, School Optimal, and Student-Truthful Many-to-One Matchings (via Differential Privacy)., , , and . SODA, page 1890-1903. SIAM, (2015)