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Surgical Fine-Tuning Improves Adaptation to Distribution Shifts.

, , , , , , и . ICLR, OpenReview.net, (2023)

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End-to-End Robotic Reinforcement Learning without Reward Engineering., , , , и . CoRR, (2019)Watch, Try, Learn: Meta-Learning from Demonstrations and Rewards., , , , , , , , , и . ICLR, OpenReview.net, (2020)Training and Evaluation of Deep Policies Using Reinforcement Learning and Generative Models., , , , , , и . J. Mach. Learn. Res., (2022)Reset-Free Guided Policy Search: Efficient Deep Reinforcement Learning with Stochastic Initial States., , , , и . CoRR, (2016)Pre-Training for Robots: Offline RL Enables Learning New Tasks in a Handful of Trials., , , , , , и . Robotics: Science and Systems, (2023)Learning Generalizable Robotic Reward Functions from "In-The-Wild" Human Videos., , и . Robotics: Science and Systems, (2021)Play it by Ear: Learning Skills amidst Occlusion through Audio-Visual Imitation Learning., , , и . Robotics: Science and Systems, (2022)BridgeData V2: A Dataset for Robot Learning at Scale., , , , , , , , , и 4 other автор(ы). CoRL, том 229 из Proceedings of Machine Learning Research, стр. 1723-1736. PMLR, (2023)Polybot: Training One Policy Across Robots While Embracing Variability., , и . CoRL, том 229 из Proceedings of Machine Learning Research, стр. 2955-2974. PMLR, (2023)Scaling Up Multi-Task Robotic Reinforcement Learning., , , , , , , и . CoRL, том 164 из Proceedings of Machine Learning Research, стр. 557-575. PMLR, (2021)