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Coupled Gradient Estimators for Discrete Latent Variables


Jun 15, 2021
Zhe Dong, Andriy Mnih, George Tucker

* Under Review 

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Autoregressive Dynamics Models for Offline Policy Evaluation and Optimization


Apr 28, 2021
Michael R. Zhang, Tom Le Paine, Ofir Nachum, Cosmin Paduraru, George Tucker, Ziyu Wang, Mohammad Norouzi

* ICLR 2021. 17 pages 

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Benchmarks for Deep Off-Policy Evaluation


Mar 30, 2021
Justin Fu, Mohammad Norouzi, Ofir Nachum, George Tucker, Ziyu Wang, Alexander Novikov, Mengjiao Yang, Michael R. Zhang, Yutian Chen, Aviral Kumar, Cosmin Paduraru, Sergey Levine, Tom Le Paine

* ICLR 2021 paper. Policies and evaluation code are available at https://github.com/google-research/deep_ope 

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Offline Policy Selection under Uncertainty


Dec 12, 2020
Mengjiao Yang, Bo Dai, Ofir Nachum, George Tucker, Dale Schuurmans


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RL Unplugged: Benchmarks for Offline Reinforcement Learning


Jul 02, 2020
Caglar Gulcehre, Ziyu Wang, Alexander Novikov, Tom Le Paine, Sergio Gomez Colmenarejo, Konrad Zolna, Rishabh Agarwal, Josh Merel, Daniel Mankowitz, Cosmin Paduraru, Gabriel Dulac-Arnold, Jerry Li, Mohammad Norouzi, Matt Hoffman, Ofir Nachum, George Tucker, Nicolas Heess, Nando de Freitas

* 21 pages including supplementary material, the github link for the datasets: https://github.com/deepmind/deepmind-research/rl_unplugged 

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Conservative Q-Learning for Offline Reinforcement Learning


Jun 29, 2020
Aviral Kumar, Aurick Zhou, George Tucker, Sergey Levine

* Preprint. Website at: https://sites.google.com/view/cql-offline-rl 

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DisARM: An Antithetic Gradient Estimator for Binary Latent Variables


Jun 18, 2020
Zhe Dong, Andriy Mnih, George Tucker


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Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems


May 04, 2020
Sergey Levine, Aviral Kumar, George Tucker, Justin Fu


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D4RL: Datasets for Deep Data-Driven Reinforcement Learning


Apr 20, 2020
Justin Fu, Aviral Kumar, Ofir Nachum, George Tucker, Sergey Levine

* Website available at https://sites.google.com/view/d4rl/home 

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Datasets for Data-Driven Reinforcement Learning


Apr 15, 2020
Justin Fu, Aviral Kumar, Ofir Nachum, George Tucker, Sergey Levine


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Meta-Learning without Memorization


Dec 24, 2019
Mingzhang Yin, George Tucker, Mingyuan Zhou, Sergey Levine, Chelsea Finn

* ICLR 2020 

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Behavior Regularized Offline Reinforcement Learning


Nov 26, 2019
Yifan Wu, George Tucker, Ofir Nachum


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Don't Blame the ELBO! A Linear VAE Perspective on Posterior Collapse


Nov 06, 2019
James Lucas, George Tucker, Roger Grosse, Mohammad Norouzi

* 11 main pages, 10 appendix pages. 13 figures total. Accepted at 33rd Conference on Neural Information Processing Systems (NeurIPS 2019) 

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Energy-Inspired Models: Learning with Sampler-Induced Distributions


Oct 31, 2019
Dieterich Lawson, George Tucker, Bo Dai, Rajesh Ranganath


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Reinforcement Learning Driven Heuristic Optimization


Jun 16, 2019
Qingpeng Cai, Will Hang, Azalia Mirhoseini, George Tucker, Jingtao Wang, Wei Wei

* DRL4KDD'19 

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Stabilizing Off-Policy Q-Learning via Bootstrapping Error Reduction


Jun 03, 2019
Aviral Kumar, Justin Fu, George Tucker, Sergey Levine


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On Variational Bounds of Mutual Information


May 16, 2019
Ben Poole, Sherjil Ozair, Aaron van den Oord, Alexander A. Alemi, George Tucker

* ICML 2019 

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Learning to Walk via Deep Reinforcement Learning


Mar 25, 2019
Tuomas Haarnoja, Sehoon Ha, Aurick Zhou, Jie Tan, George Tucker, Sergey Levine

* Videos: https://sites.google.com/view/minitaur-locomotion/ . arXiv admin note: substantial text overlap with arXiv:1812.05905 

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Model-Based Reinforcement Learning for Atari


Mar 05, 2019
Lukasz Kaiser, Mohammad Babaeizadeh, Piotr Milos, Blazej Osinski, Roy H Campbell, Konrad Czechowski, Dumitru Erhan, Chelsea Finn, Piotr Kozakowski, Sergey Levine, Ryan Sepassi, George Tucker, Henryk Michalewski


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Soft Actor-Critic Algorithms and Applications


Jan 29, 2019
Tuomas Haarnoja, Aurick Zhou, Kristian Hartikainen, George Tucker, Sehoon Ha, Jie Tan, Vikash Kumar, Henry Zhu, Abhishek Gupta, Pieter Abbeel, Sergey Levine

* arXiv admin note: substantial text overlap with arXiv:1801.01290 

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The Laplacian in RL: Learning Representations with Efficient Approximations


Oct 10, 2018
Yifan Wu, George Tucker, Ofir Nachum


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Doubly Reparameterized Gradient Estimators for Monte Carlo Objectives


Oct 09, 2018
George Tucker, Dieterich Lawson, Shixiang Gu, Chris J. Maddison


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Smoothed Action Value Functions for Learning Gaussian Policies


Jul 25, 2018
Ofir Nachum, Mohammad Norouzi, George Tucker, Dale Schuurmans

* ICML 2018 

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Sample-Efficient Reinforcement Learning with Stochastic Ensemble Value Expansion


Jul 04, 2018
Jacob Buckman, Danijar Hafner, George Tucker, Eugene Brevdo, Honglak Lee


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Guided evolutionary strategies: escaping the curse of dimensionality in random search


Jun 28, 2018
Niru Maheswaranathan, Luke Metz, George Tucker, Jascha Sohl-Dickstein


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