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Sample Amplification: Increasing Dataset Size even when Learning is Impossible., , , and . CoRR, (2019)Near-optimal Approximate Discrete and Continuous Submodular Function Minimization., , and . CoRR, (2019)Efficient Motion Planning Under Obstacle Uncertainty with Local Dependencies., and . WAFR, volume 25 of Springer Proceedings in Advanced Robotics, page 68-84. Springer, (2022)Sidestepping hardness in statistical problems.. Stanford University, USA, (2022)A Polynomial Time Algorithm for Log-Concave Maximum Likelihood via Locally Exponential Families., , , , and . NeurIPS, page 7721-7733. (2019)Near-optimal Approximate Discrete and Continuous Submodular Function Minimization., , and . SODA, page 837-853. SIAM, (2020)Provably Safe Robot Navigation with Obstacle Uncertainty., , and . Robotics: Science and Systems, (2017)Provably safe robot navigation with obstacle uncertainty., , and . Int. J. Robotics Res., (2018)Sample Amplification: Increasing Dataset Size even when Learning is Impossible., , , and . ICML, volume 119 of Proceedings of Machine Learning Research, page 442-451. PMLR, (2020)On the Statistical Complexity of Sample Amplification., , , , and . CoRR, (2022)