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Parallel Training of Deep Networks with Local Updates


Dec 07, 2020
Michael Laskin, Luke Metz, Seth Nabarrao, Mark Saroufim, Badreddine Noune, Carlo Luschi, Jascha Sohl-Dickstein, Pieter Abbeel

* First two authors - Michael Laskin and Luke Metz - contributed equally. Order was determined by a coin flip 

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Reset-Free Lifelong Learning with Skill-Space Planning


Dec 07, 2020
Kevin Lu, Aditya Grover, Pieter Abbeel, Igor Mordatch

* Website link: https://sites.google.com/berkeley.edu/reset-free-lifelong-learning 

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Trajectory-wise Multiple Choice Learning for Dynamics Generalization in Reinforcement Learning


Oct 26, 2020
Younggyo Seo, Kimin Lee, Ignasi Clavera, Thanard Kurutach, Jinwoo Shin, Pieter Abbeel

* Accepted in NeurIPS2020. First two authors contributed equally, website: https://sites.google.com/view/trajectory-mcl code: https://github.com/younggyoseo/trajectory_mcl 

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LaND: Learning to Navigate from Disengagements


Oct 09, 2020
Gregory Kahn, Pieter Abbeel, Sergey Levine


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Decoupling Representation Learning from Reinforcement Learning


Sep 30, 2020
Adam Stooke, Kimin Lee, Pieter Abbeel, Michael Laskin

* Improved related works and fixed code hyperlink 

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Visual Imitation Made Easy


Aug 11, 2020
Sarah Young, Dhiraj Gandhi, Shubham Tulsiani, Abhinav Gupta, Pieter Abbeel, Lerrel Pinto


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Hybrid Discriminative-Generative Training via Contrastive Learning


Aug 10, 2020
Hao Liu, Pieter Abbeel

* Code: https://github.com/lhao499/HDGE 

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Robust Reinforcement Learning using Adversarial Populations


Aug 04, 2020
Eugene Vinitsky, Yuqing Du, Kanaad Parvate, Kathy Jang, Pieter Abbeel, Alexandre Bayen


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Dynamics Generalization via Information Bottleneck in Deep Reinforcement Learning


Aug 03, 2020
Xingyu Lu, Kimin Lee, Pieter Abbeel, Stas Tiomkin

* 16 pages 

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