Ofir Nachum

According to our database, Ofir Nachum authored at least 72 papers between 2017 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

Q-Transformer: Scalable Offline Reinforcement Learning via Autoregressive Q-Functions.

Yevgen Chebotar, Quan Vuong, Alex Irpan, Karol Hausman, Fei Xia, Yao Lu, Aviral Kumar, Tianhe Yu, Alexander Herzog, Karl Pertsch, Keerthana Gopalakrishnan, Julian Ibarz, Ofir Nachum, Sumedh Sontakke, Grecia Salazar, Huong T. Tran, Jodilyn Peralta, Clayton Tan, Deeksha Manjunath, Jaspiar Singh, Brianna Zitkovich, Tomas Jackson, Kanishka Rao, Chelsea Finn, Sergey Levine

CoRR, 2023

Barkour: Benchmarking Animal-level Agility with Quadruped Robots.

Ken Caluwaerts, Atil Iscen, J. Chase Kew, Wenhao Yu, Tingnan Zhang, Daniel Freeman, Kuang-Huei Lee, Lisa Lee, Stefano Saliceti, Vincent Zhuang, Nathan Batchelor, Steven Bohez, Federico Casarini, Jose Enrique Chen, Omar Cortes, Erwin Coumans, Adil Dostmohamed, Gabriel Dulac-Arnold, Alejandro Escontrela, Erik Frey, Roland Hafner, Deepali Jain, Bauyrjan Jyenis, Yuheng Kuang, Tsang-Wei Edward Lee, Linda Luu, Ofir Nachum, Ken Oslund, Jason Powell, Diego Reyes, Francesco Romano, Fereshteh Sadeghi, Ron Sloat, Baruch Tabanpour, Daniel Zheng, Michael Neunert, Raia Hadsell, Nicolas Heess, Francesco Nori, Jeff Seto, Carolina Parada, Vikas Sindhwani, Vincent Vanhoucke, Jie Tan

CoRR, 2023

Multimodal Web Navigation with Instruction-Finetuned Foundation Models.

Hiroki Furuta, Ofir Nachum, Kuang-Huei Lee, Yutaka Matsuo, Shixiang Shane Gu, Izzeddin Gur

CoRR, 2023

Foundation Models for Decision Making: Problems, Methods, and Opportunities.

Sherry Yang, Ofir Nachum, Yilun Du, Jason Wei, Pieter Abbeel, Dale Schuurmans

CoRR, 2023

Learning Universal Policies via Text-Guided Video Generation.

Yilun Du, Mengjiao Yang, Bo Dai, Hanjun Dai, Ofir Nachum, Joshua B. Tenenbaum, Dale Schuurmans, Pieter Abbeel

CoRR, 2023

RT-1: Robotics Transformer for Real-World Control at Scale.

Anthony Brohan, Noah Brown, Justice Carbajal, Yevgen Chebotar, Joseph Dabis, Chelsea Finn, Keerthana Gopalakrishnan, Karol Hausman, Alexander Herzog, Jasmine Hsu, Julian Ibarz, Brian Ichter, Alex Irpan, Tomas Jackson, Sally Jesmonth, Nikhil J. Joshi, Ryan Julian, Dmitry Kalashnikov, Yuheng Kuang, Isabel Leal, Kuang-Huei Lee, Sergey Levine, Yao Lu, Utsav Malla, Deeksha Manjunath, Igor Mordatch, Ofir Nachum, Carolina Parada, Jodilyn Peralta, Emily Perez, Karl Pertsch, Jornell Quiambao, Kanishka Rao, Michael S. Ryoo, Grecia Salazar, Pannag R. Sanketi, Kevin Sayed, Jaspiar Singh, Sumedh Sontakke, Austin Stone, Clayton Tan, Huong T. Tran, Vincent Vanhoucke, Steve Vega, Quan Vuong, Fei Xia, Ted Xiao, Peng Xu, Sichun Xu, Tianhe Yu, Brianna Zitkovich

Proceedings of the Robotics: Science and Systems XIX, Daegu, 2023

Learning Universal Policies via Text-Guided Video Generation.

Yilun Du, Sherry Yang, Bo Dai, Hanjun Dai, Ofir Nachum, Josh Tenenbaum, Dale Schuurmans, Pieter Abbeel

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Inverse Dynamics Pretraining Learns Good Representations for Multitask Imitation.

David Brandfonbrener, Ofir Nachum, Joan Bruna

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Supervised Pretraining Can Learn In-Context Reinforcement Learning.

Jonathan Lee, Annie Xie, Aldo Pacchiano, Yash Chandak, Chelsea Finn, Ofir Nachum, Emma Brunskill

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Multi-Environment Pretraining Enables Transfer to Action Limited Datasets.

David Venuto, Sherry Yang, Pieter Abbeel, Doina Precup, Igor Mordatch, Ofir Nachum

Proceedings of the International Conference on Machine Learning, 2023

Dichotomy of Control: Separating What You Can Control from What You Cannot.

Sherry Yang, Dale Schuurmans, Pieter Abbeel, Ofir Nachum

Proceedings of the Eleventh International Conference on Learning Representations, 2023

A Mixture-of-Expert Approach to RL-based Dialogue Management.

Yinlam Chow, Aza Tulepbergenov, Ofir Nachum, Dhawal Gupta, Moonkyung Ryu, Mohammad Ghavamzadeh, Craig Boutilier

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Understanding HTML with Large Language Models.

Izzeddin Gur, Ofir Nachum, Yingjie Miao, Mustafa Safdari, Austin Huang, Aakanksha Chowdhery, Sharan Narang, Noah Fiedel, Aleksandra Faust

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

Contrastive Value Learning: Implicit Models for Simple Offline RL.

Bogdan Mazoure, Benjamin Eysenbach, Ofir Nachum, Jonathan Tompson

Proceedings of the Conference on Robot Learning, 2023

Q-Transformer: Scalable Offline Reinforcement Learning via Autoregressive Q-Functions.

Yevgen Chebotar, Quan Vuong, Karol Hausman, Fei Xia, Yao Lu, Alex Irpan, Aviral Kumar, Tianhe Yu, Alexander Herzog, Karl Pertsch, Keerthana Gopalakrishnan, Julian Ibarz, Ofir Nachum, Sumedh Anand Sontakke, Grecia Salazar, Huong T. Tran, Jodilyn Peralta, Clayton Tan, Deeksha Manjunath, Jaspiar Singh, Brianna Zitkovich, Tomas Jackson, Kanishka Rao, Chelsea Finn, Sergey Levine

Proceedings of the Conference on Robot Learning, 2023

2022

Dichotomy of Control: Separating What You Can Control from What You Cannot.

Mengjiao Yang, Dale Schuurmans, Pieter Abbeel, Ofir Nachum

CoRR, 2022

Joint Representation Training in Sequential Tasks with Shared Structure.

Aldo Pacchiano, Ofir Nachum, Nilesh Tripuraneni, Peter L. Bartlett

CoRR, 2022

A Mixture-of-Expert Approach to RL-based Dialogue Management.

Yinlam Chow, Aza Tulepbergenov, Ofir Nachum, Moonkyung Ryu, Mohammad Ghavamzadeh, Craig Boutilier

CoRR, 2022

Chain of Thought Imitation with Procedure Cloning.

Mengjiao Yang, Dale Schuurmans, Pieter Abbeel, Ofir Nachum

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Improving Zero-Shot Generalization in Offline Reinforcement Learning using Generalized Similarity Functions.

Bogdan Mazoure, Ilya Kostrikov, Ofir Nachum, Jonathan Tompson

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Oracle Inequalities for Model Selection in Offline Reinforcement Learning.

Jonathan N. Lee, George Tucker, Ofir Nachum, Bo Dai, Emma Brunskill

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Multi-Game Decision Transformers.

Kuang-Huei Lee, Ofir Nachum, Mengjiao Yang, Lisa Lee, Daniel Freeman, Sergio Guadarrama, Ian Fischer, Winnie Xu, Eric Jang, Henryk Michalewski, Igor Mordatch

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Why So Pessimistic? Estimating Uncertainties for Offline RL through Ensembles, and Why Their Independence Matters.

Seyed Kamyar Seyed Ghasemipour, Shixiang Shane Gu, Ofir Nachum

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

PI-ARS: Accelerating Evolution-Learned Visual-Locomotion with Predictive Information Representations.

Kuang-Huei Lee, Ofir Nachum, Tingnan Zhang, Sergio Guadarrama, Jie Tan, Wenhao Yu

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2022

Why Should I Trust You, Bellman? The Bellman Error is a Poor Replacement for Value Error.

Scott Fujimoto, David Meger, Doina Precup, Ofir Nachum, Shixiang Shane Gu

Proceedings of the International Conference on Machine Learning, 2022

Model Selection in Batch Policy Optimization.

Jonathan Lee, George Tucker, Ofir Nachum, Bo Dai

Proceedings of the International Conference on Machine Learning, 2022

TRAIL: Near-Optimal Imitation Learning with Suboptimal Data.

Mengjiao Yang, Sergey Levine, Ofir Nachum

Proceedings of the Tenth International Conference on Learning Representations, 2022

Policy Gradients Incorporating the Future.

David Venuto, Elaine Lau, Doina Precup, Ofir Nachum

Proceedings of the Tenth International Conference on Learning Representations, 2022

Offline Policy Selection under Uncertainty.

Mengjiao Yang, Bo Dai, Ofir Nachum, George Tucker, Dale Schuurmans

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Autoregressive Dynamics Models for Offline Policy Evaluation and Optimization.

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

CoRR, 2021

Near Optimal Policy Optimization via REPS.

Aldo Pacchiano, Jonathan N. Lee, Peter L. Bartlett, Ofir Nachum

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Provable Representation Learning for Imitation with Contrastive Fourier Features.

Ofir Nachum, Mengjiao Yang

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Representation Matters: Offline Pretraining for Sequential Decision Making.

Mengjiao Yang, Ofir Nachum

Proceedings of the 38th International Conference on Machine Learning, 2021

Offline Reinforcement Learning with Fisher Divergence Critic Regularization.

Ilya Kostrikov, Rob Fergus, Jonathan Tompson, Ofir Nachum

Proceedings of the 38th International Conference on Machine Learning, 2021

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

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

Proceedings of the 38th International Conference on Machine Learning, 2021

Autoregressive Dynamics Models for Offline Policy Evaluation and Optimization.

Michael R. Zhang, Thomas Paine, Ofir Nachum, Cosmin Paduraru, George Tucker, Ziyu Wang, Mohammad Norouzi

Proceedings of the 9th International Conference on Learning Representations, 2021

Deployment-Efficient Reinforcement Learning via Model-Based Offline Optimization.

Tatsuya Matsushima, Hiroki Furuta, Yutaka Matsuo, Ofir Nachum, Shixiang Gu

Proceedings of the 9th International Conference on Learning Representations, 2021

Benchmarks for Deep Off-Policy Evaluation.

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

Proceedings of the 9th International Conference on Learning Representations, 2021

OPAL: Offline Primitive Discovery for Accelerating Offline Reinforcement Learning.

Anurag Ajay, Aviral Kumar, Pulkit Agrawal, Sergey Levine, Ofir Nachum

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

Statistical Bootstrapping for Uncertainty Estimation in Off-Policy Evaluation.

Ilya Kostrikov, Ofir Nachum

CoRR, 2020

RL Unplugged: Benchmarks for Offline Reinforcement Learning.

Çaglar Gülçehre, Ziyu Wang, Alexander Novikov, Tom Le Paine, Sergio Gómez Colmenarejo, Konrad Zolna, Rishabh Agarwal, Josh Merel, Daniel J. Mankowitz, Cosmin Paduraru, Gabriel Dulac-Arnold, Jerry Li, Mohammad Norouzi, Matt Hoffman, Ofir Nachum, George Tucker, Nicolas Heess, Nando de Freitas

CoRR, 2020

D4RL: Datasets for Deep Data-Driven Reinforcement Learning.

Justin Fu, Aviral Kumar, Ofir Nachum, George Tucker, Sergey Levine

CoRR, 2020

Reinforcement Learning via Fenchel-Rockafellar Duality.

Ofir Nachum, Bo Dai

CoRR, 2020

Off-Policy Evaluation via the Regularized Lagrangian.

Mengjiao Yang, Ofir Nachum, Bo Dai, Lihong Li, Dale Schuurmans

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

CoinDICE: Off-Policy Confidence Interval Estimation.

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

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

BRPO: Batch Residual Policy Optimization.

Sungryull Sohn, Yinlam Chow, Jayden Ooi, Ofir Nachum, Honglak Lee, Ed H. Chi, Craig Boutilier

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Imitation Learning via Off-Policy Distribution Matching.

Ilya Kostrikov, Ofir Nachum, Jonathan Tompson

Proceedings of the 8th International Conference on Learning Representations, 2020

Safe Policy Learning for Continuous Control.

Yinlam Chow, Ofir Nachum, Aleksandra Faust, Edgar A. Duéñez-Guzmán, Mohammad Ghavamzadeh

Proceedings of the 4th Conference on Robot Learning, 2020

Identifying and Correcting Label Bias in Machine Learning.

Heinrich Jiang, Ofir Nachum

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

AlgaeDICE: Policy Gradient from Arbitrary Experience.

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

CoRR, 2019

Behavior Regularized Offline Reinforcement Learning.

Yifan Wu, George Tucker, Ofir Nachum

CoRR, 2019

Group-based Fair Learning Leads to Counter-intuitive Predictions.

Ofir Nachum, Heinrich Jiang

CoRR, 2019

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

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

CoRR, 2019

Lyapunov-based Safe Policy Optimization for Continuous Control.

Yinlam Chow, Ofir Nachum, Aleksandra Faust, Mohammad Ghavamzadeh, Edgar A. Duéñez-Guzmán

CoRR, 2019

DualDICE: Behavior-Agnostic Estimation of Discounted Stationary Distribution Corrections.

Ofir Nachum, Yinlam Chow, Bo Dai, Lihong Li

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

DeepMDP: Learning Continuous Latent Space Models for Representation Learning.

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

Proceedings of the 36th International Conference on Machine Learning, 2019

The Laplacian in RL: Learning Representations with Efficient Approximations.

Yifan Wu, George Tucker, Ofir Nachum

Proceedings of the 7th International Conference on Learning Representations, 2019

Near-Optimal Representation Learning for Hierarchical Reinforcement Learning.

Ofir Nachum, Shixiang Gu, Honglak Lee, Sergey Levine

Proceedings of the 7th International Conference on Learning Representations, 2019

Multi-Agent Manipulation via Locomotion using Hierarchical Sim2Real.

Ofir Nachum, Michael Ahn, Hugo Ponte, Shixiang Shane Gu, Vikash Kumar

Proceedings of the 3rd Annual Conference on Robot Learning, 2019

Robustness Guarantees for Density Clustering.

Heinrich Jiang, Jennifer Jang, Ofir Nachum

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Data-Efficient Hierarchical Reinforcement Learning.

Ofir Nachum, Shixiang Gu, Honglak Lee, Sergey Levine

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

A Lyapunov-based Approach to Safe Reinforcement Learning.

Yinlam Chow, Ofir Nachum, Edgar A. Duéñez-Guzmán, Mohammad Ghavamzadeh

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Deep Reinforcement Learning for Vision-Based Robotic Grasping: A Simulated Comparative Evaluation of Off-Policy Methods.

Deirdre Quillen, Eric Jang, Ofir Nachum, Chelsea Finn, Julian Ibarz, Sergey Levine

Proceedings of the 2018 IEEE International Conference on Robotics and Automation, 2018

Smoothed Action Value Functions for Learning Gaussian Policies.

Ofir Nachum, Mohammad Norouzi, George Tucker, Dale Schuurmans

Proceedings of the 35th International Conference on Machine Learning, 2018

Path Consistency Learning in Tsallis Entropy Regularized MDPs.

Yinlam Chow, Ofir Nachum, Mohammad Ghavamzadeh

Proceedings of the 35th International Conference on Machine Learning, 2018

Trust-PCL: An Off-Policy Trust Region Method for Continuous Control.

Ofir Nachum, Mohammad Norouzi, Kelvin Xu, Dale Schuurmans

Proceedings of the 6th International Conference on Learning Representations, 2018

MorphNet: Fast & Simple Resource-Constrained Structure Learning of Deep Networks.

Ariel Gordon, Elad Eban, Ofir Nachum, Bo Chen, Hao Wu, Tien-Ju Yang, Edward Choi

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

2017

Arboral satisfaction: Recognition and LP approximation.

Erik D. Demaine, Varun Ganesan, Vladislav Kontsevoi, Qipeng Liu, Quanquan C. Liu, Fermi Ma, Ofir Nachum, Aaron Sidford, Erik Waingarten, Daniel Ziegler

Inf. Process. Lett., 2017

MorphNet: Fast & Simple Resource-Constrained Structure Learning of Deep Networks.

Ariel Gordon, Elad Eban, Ofir Nachum, Bo Chen, Tien-Ju Yang, Edward Choi

CoRR, 2017

Bridging the Gap Between Value and Policy Based Reinforcement Learning.

Ofir Nachum, Mohammad Norouzi, Kelvin Xu, Dale Schuurmans

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Improving Policy Gradient by Exploring Under-appreciated Rewards.

Ofir Nachum, Mohammad Norouzi, Dale Schuurmans

Proceedings of the 5th International Conference on Learning Representations, 2017

Learning to Remember Rare Events.

Lukasz Kaiser, Ofir Nachum, Aurko Roy, Samy Bengio

Proceedings of the 5th International Conference on Learning Representations, 2017