Ofir Nachum
49 papers · 2017–2024 · 9 conferences · across top CS/AI conferences
Achievements
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π£ Hot Topic Early Bird π§ Keyword Pioneer πΊοΈ Taxonomy Completionist (10) π Interdisciplinary Bridge π Conference Polyglot (9)
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Mega-Team
(51)
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Conference Pioneer
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Century Club
(49)
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Trend Setter
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The Questioner
(2)
Conferences
NIPS (16)
ICLR (13)
ICML (9)
CORL (4)
AISTATS (3)
CVPR (1)
EMNLP (1)
IJCAI (1)
RSS (1)
Top co-authors
Research topics
Keywords
offline reinforcement learning
(11)
reinforcement learning
(7)
representation learning
(4)
imitation learning
(4)
policy gradient
(4)
value function
(4)
state representation
(3)
contrastive learning
(3)
off-policy evaluation
(3)
sequential decision making
(3)
policy optimization
(3)
bellman error
(3)
constraint satisfaction
(2)
model-based reinforcement learning
(2)
hierarchical reinforcement learning
(2)
multi-task learning
(2)
transfer learning
(2)
model selection
(2)
uncertainty quantification
(2)
continuous control
(2)
Papers
Multimodal Web Navigation with Instruction-Finetuned Foundation Models
ICLR 2024
Dichotomy of Control: Separating What You Can Control from What You Cannot
ICLR 2023
Learning Universal Policies via Text-Guided Video Generation
NIPS 2023
Supervised Pretraining Can Learn In-Context Reinforcement Learning
NIPS 2023
Inverse Dynamics Pretraining Learns Good Representations for Multitask Imitation
NIPS 2023
Contrastive Value Learning: Implicit Models for Simple Offline RL
CORL 2023
Q-Transformer: Scalable Offline Reinforcement Learning via Autoregressive Q-Functions
CORL 2023
Understanding HTML with Large Language Models
EMNLP 2023
A Mixture-of-Expert Approach to RL-based Dialogue Management
ICLR 2023
Multi-Environment Pretraining Enables Transfer to Action Limited Datasets
ICML 2023
RT-1: Robotics Transformer for Real-World Control at Scale
RSS 2023
Oracle Inequalities for Model Selection in Offline Reinforcement Learning
NIPS 2022
Chain of Thought Imitation with Procedure Cloning
NIPS 2022
Why Should I Trust You, Bellman? The Bellman Error is a Poor Replacement for Value Error
ICML 2022
Offline Policy Selection under Uncertainty
AISTATS 2022
Model Selection in Batch Policy Optimization
ICML 2022
TRAIL: Near-Optimal Imitation Learning with Suboptimal Data
ICLR 2022
Policy Gradients Incorporating the Future
ICLR 2022
Why So Pessimistic? Estimating Uncertainties for Offline RL through Ensembles, and Why Their Independence Matters
NIPS 2022
Improving Zero-Shot Generalization in Offline Reinforcement Learning using Generalized Similarity Functions
NIPS 2022
Multi-Game Decision Transformers
NIPS 2022
Autoregressive Dynamics Models for Offline Policy Evaluation and Optimization
ICLR 2021
Deployment-Efficient Reinforcement Learning via Model-Based Offline Optimization
ICLR 2021
OPAL: Offline Primitive Discovery for Accelerating Offline Reinforcement Learning
ICLR 2021
Near Optimal Policy Optimization via REPS
NIPS 2021
Offline Reinforcement Learning with Fisher Divergence Critic Regularization
ICML 2021
Policy Information Capacity: Information-Theoretic Measure for Task Complexity in Deep Reinforcement Learning
ICML 2021
Provable Representation Learning for Imitation with Contrastive Fourier Features
NIPS 2021
Representation Matters: Offline Pretraining for Sequential Decision Making
ICML 2021
Benchmarks for Deep Off-Policy Evaluation
ICLR 2021
Identifying and Correcting Label Bias in Machine Learning
AISTATS 2020
Off-Policy Evaluation via the Regularized Lagrangian
NIPS 2020
CoinDICE: Off-Policy Confidence Interval Estimation
NIPS 2020
Imitation Learning via Off-Policy Distribution Matching
ICLR 2020
BRPO: Batch Residual Policy Optimization
IJCAI 2020
Safe Policy Learning for Continuous Control
CORL 2020
DualDICE: Behavior-Agnostic Estimation of Discounted Stationary Distribution Corrections
NIPS 2019
DeepMDP: Learning Continuous Latent Space Models for Representation Learning
ICML 2019
The Laplacian in RL: Learning Representations with Efficient Approximations
ICLR 2019
Multi-Agent Manipulation via Locomotion using Hierarchical Sim2Real
CORL 2019
Robustness Guarantees for Density Clustering
AISTATS 2019
Near-Optimal Representation Learning for Hierarchical Reinforcement Learning
ICLR 2019
Path Consistency Learning in Tsallis Entropy Regularized MDPs
ICML 2018
Trust-PCL: An Off-Policy Trust Region Method for Continuous Control
ICLR 2018
A Lyapunov-based Approach to Safe Reinforcement Learning
NIPS 2018
MorphNet: Fast & Simple Resource-Constrained Structure Learning of Deep Networks
CVPR 2018
Smoothed Action Value Functions for Learning Gaussian Policies
ICML 2018
Data-Efficient Hierarchical Reinforcement Learning
NIPS 2018
Bridging the Gap Between Value and Policy Based Reinforcement Learning
NIPS 2017