Scott Fujimoto

35 papers A* 12Journal 21Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	—	`conf`	Imbalanced Gradients in RL Post-Training of Multi-Task LLMs. EACL (Findings) Runzhe Wu, Ankur Samanta, Ayush Jain, Scott Fujimoto, Jeongyeol Kwon, Ben Kretzu, Youliang Yu, Kaveh Hassani, Boris Vidolov, Yonathan Efroni
2026	J	`jnl`	The Surprising Difficulty of Search in Model-Based Reinforcement Learning. CoRR Wei-Di Chang, Mikael Henaff, Brandon Amos, Gregory Dudek, Scott Fujimoto
2025	A*	`conf`	Exploiting Structure in Offline Multi-Agent RL: The Benefits of Low Interaction Rank. ICLR Wenhao Zhan, Scott Fujimoto, Zheqing Zhu, Jason D. Lee, Daniel Jiang, Yonathan Efroni
2025	A*	`conf`	Generalizable Imitation Learning Through Pre-Trained Representations. ICRA Wei-Di Chang, François Robert Hogan, Scott Fujimoto, David Meger, Gregory Dudek
2025	J	`jnl`	Imbalanced Gradients in RL Post-Training of Multi-Task LLMs. CoRR Runzhe Wu, Ankur Samanta, Ayush Jain, Scott Fujimoto, Jeongyeol Kwon, Ben Kretzu, Youliang Yu, Kaveh Hassani, Boris Vidolov, Yonathan Efroni
2025	J	`jnl`	Scalable Option Learning in High-Throughput Environments. CoRR Mikael Henaff, Scott Fujimoto, Michael Matthews, Michael Rabbat
2025	J	`jnl`	Simplicial Embeddings Improve Sample Efficiency in Actor-Critic Agents. CoRR Johan S. Obando-Ceron, Walter Mayor, Samuel Lavoie, Scott Fujimoto, Aaron C. Courville, Pablo Samuel Castro
2025	J	`jnl`	Sparse-Reg: Improving Sample Complexity in Offline Reinforcement Learning using Sparsity. CoRR Samin Yeasar Arnob, Scott Fujimoto, Doina Precup
2025	A*	`conf`	Towards General-Purpose Model-Free Reinforcement Learning. ICLR Scott Fujimoto, Pierluca D'Oro, Amy Zhang, Yuandong Tian, Michael Rabbat
2025	J	`jnl`	Towards General-Purpose Model-Free Reinforcement Learning. CoRR Scott Fujimoto, Pierluca D'Oro, Amy Zhang, Yuandong Tian, Michael Rabbat
2024	J	`jnl`	Exploiting Structure in Offline Multi-Agent RL: The Benefits of Low Interaction Rank. CoRR Wenhao Zhan, Scott Fujimoto, Zheqing Zhu, Jason D. Lee, Daniel R. Jiang, Yonathan Efroni
2024	J	`jnl`	Fairness in Reinforcement Learning with Bisimulation Metrics. CoRR Sahand Rezaei-Shoshtari, Hanna Yurchyk, Scott Fujimoto, Doina Precup, David Meger
2024	J	`jnl`	Imitation Learning from Observation through Optimal Transport. RLJ Wei-Di Chang, Scott Fujimoto, David Meger, Gregory Dudek
2023	A*	`conf`	For SALE: State-Action Representation Learning for Deep Reinforcement Learning. NeurIPS Scott Fujimoto, Wei-Di Chang, Edward J. Smith, Shixiang Gu, Doina Precup, David Meger
2023	J	`jnl`	For SALE: State-Action Representation Learning for Deep Reinforcement Learning. CoRR Scott Fujimoto, Wei-Di Chang, Edward J. Smith, Shixiang Shane Gu, Doina Precup, David Meger
2023	J	`jnl`	Imitation Learning from Observation through Optimal Transport. CoRR Wei-Di Chang, Scott Fujimoto, David Meger, Gregory Dudek
2022	J	`jnl`	IL-flOw: Imitation Learning from Observation using Normalizing Flows. CoRR Wei-Di Chang, Juan Camilo Gamboa Higuera, Scott Fujimoto, David Meger, Gregory Dudek
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
2021	A*	`conf`	A Deep Reinforcement Learning Approach to Marginalized Importance Sampling with the Successor Representation. ICML Scott Fujimoto, David Meger, Doina Precup
2021	J	`jnl`	A Deep Reinforcement Learning Approach to Marginalized Importance Sampling with the Successor Representation. CoRR Scott Fujimoto, David Meger, Doina Precup
2021	A*	`conf`	A Minimalist Approach to Offline Reinforcement Learning. NeurIPS Scott Fujimoto, Shixiang Shane Gu
2021	J	`jnl`	A Minimalist Approach to Offline Reinforcement Learning. CoRR Scott Fujimoto, Shixiang Shane Gu
2020	A*	`conf`	An Equivalence between Loss Functions and Non-Uniform Sampling in Experience Replay. NeurIPS Scott Fujimoto, David Meger, Doina Precup
2020	J	`jnl`	An Equivalence between Loss Functions and Non-Uniform Sampling in Experience Replay. CoRR Scott Fujimoto, David Meger, Doina Precup
2019	J	`jnl`	Benchmarking Batch Deep Reinforcement Learning Algorithms. CoRR Scott Fujimoto, Edoardo Conti, Mohammad Ghavamzadeh, Joelle Pineau
2019	A*	`conf`	GEOMetrics: Exploiting Geometric Structure for Graph-Encoded Objects. ICML Edward J. Smith, Scott Fujimoto, Adriana Romero, David Meger
2019	J	`jnl`	GEOMetrics: Exploiting Geometric Structure for Graph-Encoded Objects. CoRR Edward J. Smith, Scott Fujimoto, Adriana Romero, David Meger
2019	A*	`conf`	Off-Policy Deep Reinforcement Learning without Exploration. ICML Scott Fujimoto, David Meger, Doina Precup
2018	J	`jnl`	3D Object Super-Resolution. CoRR Edward J. Smith, Scott Fujimoto, David Meger
2018	A*	`conf`	Addressing Function Approximation Error in Actor-Critic Methods. ICML Scott Fujimoto, Herke van Hoof, David Meger
2018	J	`jnl`	Addressing Function Approximation Error in Actor-Critic Methods. CoRR Scott Fujimoto, Herke van Hoof, David Meger
2018	A*	`conf`	Multi-View Silhouette and Depth Decomposition for High Resolution 3D Object Representation. NeurIPS Edward J. Smith, Scott Fujimoto, David Meger
2018	J	`jnl`	Off-Policy Deep Reinforcement Learning without Exploration. CoRR Scott Fujimoto, David Meger, Doina Precup
2018	—	`conf`	Sentiment Analysis: It's Complicated! NAACL-HLT Kian Kenyon-Dean, Eisha Ahmed, Scott Fujimoto, Jeremy Georges-Filteau, Christopher Glasz, Barleen Kaur, Auguste Lalande, Shruti Bhanderi, Robert Belfer, Nirmal Kanagasabai, Roman Sarrazingendron, Rohit Verma, Derek Ruths