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Provable Representation Learning for Imitation with Contrastive Fourier Features

May 26, 2021
Ofir Nachum, Mengjiao Yang

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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 

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Policy Information Capacity: Information-Theoretic Measure for Task Complexity in Deep Reinforcement Learning

Mar 23, 2021
Hiroki Furuta, Tatsuya Matsushima, Tadashi Kozuno, Yutaka Matsuo, Sergey Levine, Ofir Nachum, Shixiang Shane Gu

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Near Optimal Policy Optimization via REPS

Mar 17, 2021
Aldo Pacchiano, Jonathan Lee, Peter Bartlett, Ofir Nachum

* 8 main pages, 37 total pages 

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Offline Reinforcement Learning with Fisher Divergence Critic Regularization

Mar 14, 2021
Ilya Kostrikov, Jonathan Tompson, Rob Fergus, Ofir Nachum

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Representation Matters: Offline Pretraining for Sequential Decision Making

Feb 11, 2021
Mengjiao Yang, Ofir Nachum

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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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OPAL: Offline Primitive Discovery for Accelerating Offline Reinforcement Learning

Oct 27, 2020
Anurag Ajay, Aviral Kumar, Pulkit Agrawal, Sergey Levine, Ofir Nachum


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CoinDICE: Off-Policy Confidence Interval Estimation

Oct 22, 2020
Bo Dai, Ofir Nachum, Yinlam Chow, Lihong Li, Csaba Szepesvári, Dale Schuurmans

* To appear at NeurIPS 2020 as spotlight 

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Statistical Bootstrapping for Uncertainty Estimation in Off-Policy Evaluation

Jul 27, 2020
Ilya Kostrikov, Ofir Nachum

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Off-Policy Evaluation via the Regularized Lagrangian

Jul 07, 2020
Mengjiao Yang, Ofir Nachum, Bo Dai, Lihong Li, 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: 

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Deployment-Efficient Reinforcement Learning via Model-Based Offline Optimization

Jun 23, 2020
Tatsuya Matsushima, Hiroki Furuta, Yutaka Matsuo, Ofir Nachum, Shixiang Gu

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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 

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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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BRPO: Batch Residual Policy Optimization

Feb 08, 2020
Sungryull Sohn, Yinlam Chow, Jayden Ooi, Ofir Nachum, Honglak Lee, Ed Chi, Craig Boutilier

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Reinforcement Learning via Fenchel-Rockafellar Duality

Jan 09, 2020
Ofir Nachum, Bo Dai

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Imitation Learning via Off-Policy Distribution Matching

Dec 10, 2019
Ilya Kostrikov, Ofir Nachum, Jonathan Tompson

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AlgaeDICE: Policy Gradient from Arbitrary Experience

Dec 04, 2019
Ofir Nachum, Bo Dai, Ilya Kostrikov, Yinlam Chow, Lihong Li, Dale Schuurmans

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Behavior Regularized Offline Reinforcement Learning

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

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Group-based Fair Learning Leads to Counter-intuitive Predictions

Oct 04, 2019
Ofir Nachum, Heinrich Jiang

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Why Does Hierarchy (Sometimes) Work So Well in Reinforcement Learning?

Sep 23, 2019
Ofir Nachum, Haoran Tang, Xingyu Lu, Shixiang Gu, Honglak Lee, Sergey Levine

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Multi-Agent Manipulation via Locomotion using Hierarchical Sim2Real

Aug 13, 2019
Ofir Nachum, Michael Ahn, Hugo Ponte, Shixiang Gu, Vikash Kumar

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DualDICE: Behavior-Agnostic Estimation of Discounted Stationary Distribution Corrections

Jun 10, 2019
Ofir Nachum, Yinlam Chow, Bo Dai, Lihong Li

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DeepMDP: Learning Continuous Latent Space Models for Representation Learning

Jun 06, 2019
Carles Gelada, Saurabh Kumar, Jacob Buckman, Ofir Nachum, Marc G. Bellemare

* 13 pages main text, 16 pages appendix. ICML 2019 

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Lyapunov-based Safe Policy Optimization for Continuous Control

Jan 28, 2019
Yinlam Chow, Ofir Nachum, Aleksandra Faust, Mohammad Ghavamzadeh, Edgar Duenez-Guzman

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