Ofir Nachum - RankMe

119 papers A* 37A 5Misc 4Journal 65Unranked 8

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Why Language Models Hallucinate. CoRR Adam Tauman Kalai, Ofir Nachum, Santosh S. Vempala, Edwin Zhang
2024	A*	`conf`	Multimodal Web Navigation with Instruction-Finetuned Foundation Models. ICLR Hiroki Furuta, Kuang-Huei Lee, Ofir Nachum, Yutaka Matsuo, Aleksandra Faust, Shixiang Shane Gu, Izzeddin Gur
2024	A	`conf`	The Design of the Barkour Benchmark for Robot Agility. IROS Wenhao Yu, Ken Caluwaerts, Atil Iscen, J. Chase Kew, Tingnan Zhang, Daniel Freeman, Lisa Lee, Stefano Saliceti, Vincent Zhuang, Nathan Batchelor, Steven Bohez, Federico Casarini, José Enrique Chen, Erwin Coumans, Adil Dostmohamed, Gabriel Dulac-Arnold, Alejandro Escontrela, Erik Frey, Roland Hafner, Deepali Jain, Bauyrjan Jyenis, Yuheng Kuang, Tsang-Wei Edward Lee, Ofir Nachum, Ken Oslund, Francesco Romano, Fereshteh Sadeghi, Baruch Tabanpour, Daniel Zheng, Michael Neunert, Raia Hadsell, Nicolas Heess, Francesco Nori, Jeff Seto, Carolina Parada, Vikas Sindhwani, Vincent Vanhoucke, Jie Tan, Kuang-Huei Lee
2023	A*	`conf`	A Mixture-of-Expert Approach to RL-based Dialogue Management. ICLR Yinlam Chow, Aza Tulepbergenov, Ofir Nachum, Dhawal Gupta, Moonkyung Ryu, Mohammad Ghavamzadeh, Craig Boutilier
2023	J	`jnl`	Barkour: Benchmarking Animal-level Agility with Quadruped Robots. CoRR 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, José 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
2023	Misc	`conf`	Contrastive Value Learning: Implicit Models for Simple Offline RL. CoRL Bogdan Mazoure, Benjamin Eysenbach, Ofir Nachum, Jonathan Tompson
2023	A*	`conf`	Dichotomy of Control: Separating What You Can Control from What You Cannot. ICLR Sherry Yang, Dale Schuurmans, Pieter Abbeel, Ofir Nachum
2023	J	`jnl`	Foundation Models for Decision Making: Problems, Methods, and Opportunities. CoRR Sherry Yang, Ofir Nachum, Yilun Du, Jason Wei, Pieter Abbeel, Dale Schuurmans
2023	A*	`conf`	Inverse Dynamics Pretraining Learns Good Representations for Multitask Imitation. NeurIPS David Brandfonbrener, Ofir Nachum, Joan Bruna
2023	J	`jnl`	Inverse Dynamics Pretraining Learns Good Representations for Multitask Imitation. CoRR David Brandfonbrener, Ofir Nachum, Joan Bruna
2023	A*	`conf`	Learning Universal Policies via Text-Guided Video Generation. NeurIPS Yilun Du, Sherry Yang, Bo Dai, Hanjun Dai, Ofir Nachum, Josh Tenenbaum, Dale Schuurmans, Pieter Abbeel
2023	J	`jnl`	Learning Universal Policies via Text-Guided Video Generation. CoRR Yilun Du, Mengjiao Yang, Bo Dai, Hanjun Dai, Ofir Nachum, Joshua B. Tenenbaum, Dale Schuurmans, Pieter Abbeel
2023	A*	`conf`	Multi-Environment Pretraining Enables Transfer to Action Limited Datasets. ICML David Venuto, Sherry Yang, Pieter Abbeel, Doina Precup, Igor Mordatch, Ofir Nachum
2023	J	`jnl`	Multimodal Web Navigation with Instruction-Finetuned Foundation Models. CoRR Hiroki Furuta, Ofir Nachum, Kuang-Huei Lee, Yutaka Matsuo, Shixiang Shane Gu, Izzeddin Gur
2023	Misc	`conf`	Q-Transformer: Scalable Offline Reinforcement Learning via Autoregressive Q-Functions. CoRL 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
2023	J	`jnl`	Q-Transformer: Scalable Offline Reinforcement Learning via Autoregressive Q-Functions. CoRR 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
2023	—	`conf`	RT-1: Robotics Transformer for Real-World Control at Scale. Robotics: Science and Systems 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
2023	A*	`conf`	Supervised Pretraining Can Learn In-Context Reinforcement Learning. NeurIPS Jonathan Lee, Annie Xie, Aldo Pacchiano, Yash Chandak, Chelsea Finn, Ofir Nachum, Emma Brunskill
2023	J	`jnl`	Supervised Pretraining Can Learn In-Context Reinforcement Learning. CoRR Jonathan N. Lee, Annie Xie, Aldo Pacchiano, Yash Chandak, Chelsea Finn, Ofir Nachum, Emma Brunskill
2023	—	`conf`	Understanding HTML with Large Language Models. EMNLP (Findings) Izzeddin Gur, Ofir Nachum, Yingjie Miao, Mustafa Safdari, Austin V. Huang, Aakanksha Chowdhery, Sharan Narang, Noah Fiedel, Aleksandra Faust
2022	J	`jnl`	A Mixture-of-Expert Approach to RL-based Dialogue Management. CoRR Yinlam Chow, Aza Tulepbergenov, Ofir Nachum, Moonkyung Ryu, Mohammad Ghavamzadeh, Craig Boutilier
2022	A*	`conf`	Chain of Thought Imitation with Procedure Cloning. NeurIPS Mengjiao Yang, Dale Schuurmans, Pieter Abbeel, Ofir Nachum
2022	J	`jnl`	Chain of Thought Imitation with Procedure Cloning. CoRR Mengjiao Yang, Dale Schuurmans, Pieter Abbeel, Ofir Nachum
2022	J	`jnl`	Contrastive Value Learning: Implicit Models for Simple Offline RL. CoRR Bogdan Mazoure, Benjamin Eysenbach, Ofir Nachum, Jonathan Tompson
2022	J	`jnl`	Dichotomy of Control: Separating What You Can Control from What You Cannot. CoRR Mengjiao Yang, Dale Schuurmans, Pieter Abbeel, Ofir Nachum
2022	A*	`conf`	Improving Zero-Shot Generalization in Offline Reinforcement Learning using Generalized Similarity Functions. NeurIPS Bogdan Mazoure, Ilya Kostrikov, Ofir Nachum, Jonathan Tompson
2022	J	`jnl`	Joint Representation Training in Sequential Tasks with Shared Structure. CoRR Aldo Pacchiano, Ofir Nachum, Nilesh Tripuraneni, Peter L. Bartlett
2022	A*	`conf`	Model Selection in Batch Policy Optimization. ICML Jonathan Lee, George Tucker, Ofir Nachum, Bo Dai
2022	J	`jnl`	Multi-Environment Pretraining Enables Transfer to Action Limited Datasets. CoRR David Venuto, Sherry Yang, Pieter Abbeel, Doina Precup, Igor Mordatch, Ofir Nachum
2022	A*	`conf`	Multi-Game Decision Transformers. NeurIPS Kuang-Huei Lee, Ofir Nachum, Mengjiao Yang, Lisa Lee, Daniel Freeman, Sergio Guadarrama, Ian Fischer, Winnie Xu, Eric Jang, Henryk Michalewski, Igor Mordatch
2022	J	`jnl`	Multi-Game Decision Transformers. CoRR Kuang-Huei Lee, Ofir Nachum, Mengjiao Yang, Lisa Lee, Daniel Freeman, Winnie Xu, Sergio Guadarrama, Ian Fischer, Eric Jang, Henryk Michalewski, Igor Mordatch
2022	A	`conf`	Offline Policy Selection under Uncertainty. AISTATS Mengjiao Yang, Bo Dai, Ofir Nachum, George Tucker, Dale Schuurmans
2022	A*	`conf`	Oracle Inequalities for Model Selection in Offline Reinforcement Learning. NeurIPS Jonathan N. Lee, George Tucker, Ofir Nachum, Bo Dai, Emma Brunskill
2022	J	`jnl`	Oracle Inequalities for Model Selection in Offline Reinforcement Learning. CoRR Jonathan N. Lee, George Tucker, Ofir Nachum, Bo Dai, Emma Brunskill
2022	A	`conf`	PI-ARS: Accelerating Evolution-Learned Visual-Locomotion with Predictive Information Representations. IROS Kuang-Huei Lee, Ofir Nachum, Tingnan Zhang, Sergio Guadarrama, Jie Tan, Wenhao Yu
2022	J	`jnl`	PI-ARS: Accelerating Evolution-Learned Visual-Locomotion with Predictive Information Representations. CoRR Kuang-Huei Lee, Ofir Nachum, Tingnan Zhang, Sergio Guadarrama, Jie Tan, Wenhao Yu
2022	A*	`conf`	Policy Gradients Incorporating the Future. ICLR David Venuto, Elaine Lau, Doina Precup, Ofir Nachum
2022	J	`jnl`	RT-1: Robotics Transformer for Real-World Control at Scale. CoRR 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 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
2022	A*	`conf`	TRAIL: Near-Optimal Imitation Learning with Suboptimal Data. ICLR Mengjiao Yang, Sergey Levine, Ofir Nachum
2022	J	`jnl`	Understanding HTML with Large Language Models. CoRR Izzeddin Gur, Ofir Nachum, Yingjie Miao, Mustafa Safdari, Austin V. Huang, Aakanksha Chowdhery, Sharan Narang, Noah Fiedel, Aleksandra Faust
2022	A*	`conf`	Why Should I Trust You, Bellman? The Bellman Error is a Poor Replacement for Value Error. ICML Scott Fujimoto, David Meger, Doina Precup, Ofir Nachum, Shixiang Shane Gu
2022	J	`jnl`	Why Should I Trust You, Bellman? The Bellman Error is a Poor Replacement for Value Error. CoRR Scott Fujimoto, David Meger, Doina Precup, Ofir Nachum, Shixiang Shane Gu
2022	A*	`conf`	Why So Pessimistic? Estimating Uncertainties for Offline RL through Ensembles, and Why Their Independence Matters. NeurIPS Seyed Kamyar Seyed Ghasemipour, Shixiang Shane Gu, Ofir Nachum
2022	J	`jnl`	Why So Pessimistic? Estimating Uncertainties for Offline RL through Ensembles, and Why Their Independence Matters. CoRR Seyed Kamyar Seyed Ghasemipour, Shixiang Shane Gu, Ofir Nachum
2021	A*	`conf`	Autoregressive Dynamics Models for Offline Policy Evaluation and Optimization. ICLR Michael R. Zhang, Thomas Paine, Ofir Nachum, Cosmin Paduraru, George Tucker, Ziyu Wang, Mohammad Norouzi
2021	J	`jnl`	Autoregressive Dynamics Models for Offline Policy Evaluation and Optimization. CoRR Michael R. Zhang, Tom Le Paine, Ofir Nachum, Cosmin Paduraru, George Tucker, Ziyu Wang, Mohammad Norouzi
2021	A*	`conf`	Benchmarks for Deep Off-Policy Evaluation. ICLR 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
2021	J	`jnl`	Benchmarks for Deep Off-Policy Evaluation. CoRR 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
2021	A*	`conf`	Deployment-Efficient Reinforcement Learning via Model-Based Offline Optimization. ICLR Tatsuya Matsushima, Hiroki Furuta, Yutaka Matsuo, Ofir Nachum, Shixiang Gu
2021	J	`jnl`	Improving Zero-shot Generalization in Offline Reinforcement Learning using Generalized Similarity Functions. CoRR Bogdan Mazoure, Ilya Kostrikov, Ofir Nachum, Jonathan Tompson
2021	J	`jnl`	Model Selection in Batch Policy Optimization. CoRR Jonathan N. Lee, George Tucker, Ofir Nachum, Bo Dai
2021	A*	`conf`	Near Optimal Policy Optimization via REPS. NeurIPS Aldo Pacchiano, Jonathan N. Lee, Peter L. Bartlett, Ofir Nachum
2021	J	`jnl`	Near Optimal Policy Optimization via REPS. CoRR Aldo Pacchiano, Jonathan N. Lee, Peter L. Bartlett, Ofir Nachum
2021	A*	`conf`	OPAL: Offline Primitive Discovery for Accelerating Offline Reinforcement Learning. ICLR Anurag Ajay, Aviral Kumar, Pulkit Agrawal, Sergey Levine, Ofir Nachum
2021	A*	`conf`	Offline Reinforcement Learning with Fisher Divergence Critic Regularization. ICML Ilya Kostrikov, Rob Fergus, Jonathan Tompson, Ofir Nachum
2021	J	`jnl`	Offline Reinforcement Learning with Fisher Divergence Critic Regularization. CoRR Ilya Kostrikov, Jonathan Tompson, Rob Fergus, Ofir Nachum
2021	J	`jnl`	Policy Gradients Incorporating the Future. CoRR David Venuto, Elaine Lau, Doina Precup, Ofir Nachum
2021	A*	`conf`	Policy Information Capacity: Information-Theoretic Measure for Task Complexity in Deep Reinforcement Learning. ICML Hiroki Furuta, Tatsuya Matsushima, Tadashi Kozuno, Yutaka Matsuo, Sergey Levine, Ofir Nachum, Shixiang Shane Gu
2021	J	`jnl`	Policy Information Capacity: Information-Theoretic Measure for Task Complexity in Deep Reinforcement Learning. CoRR Hiroki Furuta, Tatsuya Matsushima, Tadashi Kozuno, Yutaka Matsuo, Sergey Levine, Ofir Nachum, Shixiang Shane Gu
2021	A*	`conf`	Provable Representation Learning for Imitation with Contrastive Fourier Features. NeurIPS Ofir Nachum, Mengjiao Yang
2021	J	`jnl`	Provable Representation Learning for Imitation with Contrastive Fourier Features. CoRR Ofir Nachum, Mengjiao Yang
2021	A*	`conf`	Representation Matters: Offline Pretraining for Sequential Decision Making. ICML Mengjiao Yang, Ofir Nachum
2021	J	`jnl`	Representation Matters: Offline Pretraining for Sequential Decision Making. CoRR Mengjiao Yang, Ofir Nachum
2021	J	`jnl`	TRAIL: Near-Optimal Imitation Learning with Suboptimal Data. CoRR Mengjiao Yang, Sergey Levine, Ofir Nachum
2020	A*	`conf`	BRPO: Batch Residual Policy Optimization. IJCAI Sungryull Sohn, Yinlam Chow, Jayden Ooi, Ofir Nachum, Honglak Lee, Ed H. Chi, Craig Boutilier
2020	J	`jnl`	BRPO: Batch Residual Policy Optimization. CoRR Sungryull Sohn, Yinlam Chow, Jayden Ooi, Ofir Nachum, Honglak Lee, Ed H. Chi, Craig Boutilier
2020	A*	`conf`	CoinDICE: Off-Policy Confidence Interval Estimation. NeurIPS Bo Dai, Ofir Nachum, Yinlam Chow, Lihong Li, Csaba Szepesvári, Dale Schuurmans
2020	J	`jnl`	CoinDICE: Off-Policy Confidence Interval Estimation. CoRR Bo Dai, Ofir Nachum, Yinlam Chow, Lihong Li, Csaba Szepesvári, Dale Schuurmans
2020	J	`jnl`	D4RL: Datasets for Deep Data-Driven Reinforcement Learning. CoRR Justin Fu, Aviral Kumar, Ofir Nachum, George Tucker, Sergey Levine
2020	J	`jnl`	Deployment-Efficient Reinforcement Learning via Model-Based Offline Optimization. CoRR Tatsuya Matsushima, Hiroki Furuta, Yutaka Matsuo, Ofir Nachum, Shixiang Gu
2020	A	`conf`	Identifying and Correcting Label Bias in Machine Learning. AISTATS Heinrich Jiang, Ofir Nachum
2020	A*	`conf`	Imitation Learning via Off-Policy Distribution Matching. ICLR Ilya Kostrikov, Ofir Nachum, Jonathan Tompson
2020	J	`jnl`	OPAL: Offline Primitive Discovery for Accelerating Offline Reinforcement Learning. CoRR Anurag Ajay, Aviral Kumar, Pulkit Agrawal, Sergey Levine, Ofir Nachum
2020	A*	`conf`	Off-Policy Evaluation via the Regularized Lagrangian. NeurIPS Mengjiao Yang, Ofir Nachum, Bo Dai, Lihong Li, Dale Schuurmans
2020	J	`jnl`	Off-Policy Evaluation via the Regularized Lagrangian. CoRR Mengjiao Yang, Ofir Nachum, Bo Dai, Lihong Li, Dale Schuurmans
2020	J	`jnl`	Offline Policy Selection under Uncertainty. CoRR Mengjiao Yang, Bo Dai, Ofir Nachum, George Tucker, Dale Schuurmans
2020	J	`jnl`	RL Unplugged: Benchmarks for Offline Reinforcement Learning. CoRR 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
2020	J	`jnl`	Reinforcement Learning via Fenchel-Rockafellar Duality. CoRR Ofir Nachum, Bo Dai
2020	Misc	`conf`	Safe Policy Learning for Continuous Control. CoRL Yinlam Chow, Ofir Nachum, Aleksandra Faust, Edgar A. Duéñez-Guzmán, Mohammad Ghavamzadeh
2020	J	`jnl`	Statistical Bootstrapping for Uncertainty Estimation in Off-Policy Evaluation. CoRR Ilya Kostrikov, Ofir Nachum
2019	J	`jnl`	AlgaeDICE: Policy Gradient from Arbitrary Experience. CoRR Ofir Nachum, Bo Dai, Ilya Kostrikov, Yinlam Chow, Lihong Li, Dale Schuurmans
2019	J	`jnl`	Behavior Regularized Offline Reinforcement Learning. CoRR Yifan Wu, George Tucker, Ofir Nachum
2019	A*	`conf`	DeepMDP: Learning Continuous Latent Space Models for Representation Learning. ICML Carles Gelada, Saurabh Kumar, Jacob Buckman, Ofir Nachum, Marc G. Bellemare
2019	J	`jnl`	DeepMDP: Learning Continuous Latent Space Models for Representation Learning. CoRR Carles Gelada, Saurabh Kumar, Jacob Buckman, Ofir Nachum, Marc G. Bellemare
2019	A*	`conf`	DualDICE: Behavior-Agnostic Estimation of Discounted Stationary Distribution Corrections. NeurIPS Ofir Nachum, Yinlam Chow, Bo Dai, Lihong Li
2019	J	`jnl`	DualDICE: Behavior-Agnostic Estimation of Discounted Stationary Distribution Corrections. CoRR Ofir Nachum, Yinlam Chow, Bo Dai, Lihong Li
2019	J	`jnl`	Group-based Fair Learning Leads to Counter-intuitive Predictions. CoRR Ofir Nachum, Heinrich Jiang
2019	J	`jnl`	Identifying and Correcting Label Bias in Machine Learning. CoRR Heinrich Jiang, Ofir Nachum
2019	J	`jnl`	Imitation Learning via Off-Policy Distribution Matching. CoRR Ilya Kostrikov, Ofir Nachum, Jonathan Tompson
2019	J	`jnl`	Lyapunov-based Safe Policy Optimization for Continuous Control. CoRR Yinlam Chow, Ofir Nachum, Aleksandra Faust, Mohammad Ghavamzadeh, Edgar A. Duéñez-Guzmán
2019	Misc	`conf`	Multi-Agent Manipulation via Locomotion using Hierarchical Sim2Real. CoRL Ofir Nachum, Michael Ahn, Hugo Ponte, Shixiang Shane Gu, Vikash Kumar
2019	J	`jnl`	Multi-Agent Manipulation via Locomotion using Hierarchical Sim2Real. CoRR Ofir Nachum, Michael Ahn, Hugo Ponte, Shixiang Gu, Vikash Kumar
2019	—	`conf`	Near-Optimal Representation Learning for Hierarchical Reinforcement Learning. ICLR (Poster) Ofir Nachum, Shixiang Gu, Honglak Lee, Sergey Levine
2019	A	`conf`	Robustness Guarantees for Density Clustering. AISTATS Heinrich Jiang, Jennifer Jang, Ofir Nachum
2019	—	`conf`	The Laplacian in RL: Learning Representations with Efficient Approximations. ICLR (Poster) Yifan Wu, George Tucker, Ofir Nachum
2019	J	`jnl`	Why Does Hierarchy (Sometimes) Work So Well in Reinforcement Learning? CoRR Ofir Nachum, Haoran Tang, Xingyu Lu, Shixiang Gu, Honglak Lee, Sergey Levine
2018	A*	`conf`	A Lyapunov-based Approach to Safe Reinforcement Learning. NeurIPS Yinlam Chow, Ofir Nachum, Edgar A. Duéñez-Guzmán, Mohammad Ghavamzadeh
2018	J	`jnl`	A Lyapunov-based Approach to Safe Reinforcement Learning. CoRR Yinlam Chow, Ofir Nachum, Edgar A. Duéñez-Guzmán, Mohammad Ghavamzadeh
2018	A*	`conf`	Data-Efficient Hierarchical Reinforcement Learning. NeurIPS Ofir Nachum, Shixiang Gu, Honglak Lee, Sergey Levine
2018	J	`jnl`	Data-Efficient Hierarchical Reinforcement Learning. CoRR Ofir Nachum, Shixiang Gu, Honglak Lee, Sergey Levine
2018	A*	`conf`	Deep Reinforcement Learning for Vision-Based Robotic Grasping: A Simulated Comparative Evaluation of Off-Policy Methods. ICRA Deirdre Quillen, Eric Jang, Ofir Nachum, Chelsea Finn, Julian Ibarz, Sergey Levine
2018	J	`jnl`	Deep Reinforcement Learning for Vision-Based Robotic Grasping: A Simulated Comparative Evaluation of Off-Policy Methods. CoRR Deirdre Quillen, Eric Jang, Ofir Nachum, Chelsea Finn, Julian Ibarz, Sergey Levine
2018	A*	`conf`	MorphNet: Fast & Simple Resource-Constrained Structure Learning of Deep Networks. CVPR Ariel Gordon, Elad Eban, Ofir Nachum, Bo Chen, Hao Wu, Tien-Ju Yang, Edward Choi
2018	J	`jnl`	Near-Optimal Representation Learning for Hierarchical Reinforcement Learning. CoRR Ofir Nachum, Shixiang Gu, Honglak Lee, Sergey Levine
2018	A*	`conf`	Path Consistency Learning in Tsallis Entropy Regularized MDPs. ICML Yinlam Chow, Ofir Nachum, Mohammad Ghavamzadeh
2018	J	`jnl`	Path Consistency Learning in Tsallis Entropy Regularized MDPs. CoRR Ofir Nachum, Yinlam Chow, Mohammad Ghavamzadeh
2018	A*	`conf`	Smoothed Action Value Functions for Learning Gaussian Policies. ICML Ofir Nachum, Mohammad Norouzi, George Tucker, Dale Schuurmans
2018	J	`jnl`	Smoothed Action Value Functions for Learning Gaussian Policies. CoRR Ofir Nachum, Mohammad Norouzi, George Tucker, Dale Schuurmans
2018	J	`jnl`	The Laplacian in RL: Learning Representations with Efficient Approximations. CoRR Yifan Wu, George Tucker, Ofir Nachum
2018	—	`conf`	Trust-PCL: An Off-Policy Trust Region Method for Continuous Control. ICLR (Poster) Ofir Nachum, Mohammad Norouzi, Kelvin Xu, Dale Schuurmans
2017	J	`jnl`	Arboral satisfaction: Recognition and LP approximation. Inf. Process. Lett. Erik D. Demaine, Varun Ganesan, Vladislav Kontsevoi, Qipeng Liu, Quanquan C. Liu, Fermi Ma, Ofir Nachum, Aaron Sidford, Erik Waingarten, Daniel Ziegler
2017	—	`conf`	Bridging the Gap Between Value and Policy Based Reinforcement Learning. NIPS Ofir Nachum, Mohammad Norouzi, Kelvin Xu, Dale Schuurmans
2017	J	`jnl`	Bridging the Gap Between Value and Policy Based Reinforcement Learning. CoRR Ofir Nachum, Mohammad Norouzi, Kelvin Xu, Dale Schuurmans
2017	—	`conf`	Improving Policy Gradient by Exploring Under-appreciated Rewards. ICLR (Poster) Ofir Nachum, Mohammad Norouzi, Dale Schuurmans
2017	—	`conf`	Learning to Remember Rare Events. ICLR (Poster) Lukasz Kaiser, Ofir Nachum, Aurko Roy, Samy Bengio
2017	J	`jnl`	Learning to Remember Rare Events. CoRR Lukasz Kaiser, Ofir Nachum, Aurko Roy, Samy Bengio
2017	J	`jnl`	MorphNet: Fast & Simple Resource-Constrained Structure Learning of Deep Networks. CoRR Ariel Gordon, Elad Eban, Ofir Nachum, Bo Chen, Tien-Ju Yang, Edward Choi
2017	J	`jnl`	Trust-PCL: An Off-Policy Trust Region Method for Continuous Control. CoRR Ofir Nachum, Mohammad Norouzi, Kelvin Xu, Dale Schuurmans
2016	J	`jnl`	Improving Policy Gradient by Exploring Under-appreciated Rewards. CoRR Ofir Nachum, Mohammad Norouzi, Dale Schuurmans