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Provably Robust Blackbox Optimization for Reinforcement Learning., , , , , , , , and . CoRL, volume 100 of Proceedings of Machine Learning Research, page 683-696. PMLR, (2019)Practical Nonisotropic Monte Carlo Sampling in High Dimensions via Determinantal Point Processes., , , and . AISTATS, volume 108 of Proceedings of Machine Learning Research, page 1363-1374. PMLR, (2020)Human-Timescale Adaptation in an Open-Ended Task Space., , , , , , , , , and 18 other author(s). CoRR, (2023)On Optimism in Model-Based Reinforcement Learning., , , , and . CoRR, (2020)Towards tractable optimism in model-based reinforcement learning., , , , and . UAI, volume 161 of Proceedings of Machine Learning Research, page 1413-1423. AUAI Press, (2021)From Complexity to Simplicity: Adaptive ES-Active Subspaces for Blackbox Optimization., , , , and . NeurIPS, page 10299-10309. (2019)Ready Policy One: World Building Through Active Learning., , , , and . ICML, volume 119 of Proceedings of Machine Learning Research, page 591-601. PMLR, (2020)Towards an Understanding of Default Policies in Multitask Policy Optimization., , , and . AISTATS, volume 151 of Proceedings of Machine Learning Research, page 10661-10686. PMLR, (2022)MiniHack the Planet: A Sandbox for Open-Ended Reinforcement Learning Research., , , , , , , , , and . NeurIPS Datasets and Benchmarks, (2021)Replay-Guided Adversarial Environment Design., , , , , and . NeurIPS, page 1884-1897. (2021)