Wen Sun - RankMe

170 papers A* 65A 6C 3Journal 91Unranked 4

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	KARL: Knowledge Agents via Reinforcement Learning. CoRR Jonathan D. Chang, Andrew Drozdov, Shubham Toshniwal, Owen Oertell, Alexander Trott, Jacob P. Portes, Abhay Gupta, Pallavi Koppol, Ashutosh Baheti, Sean Kulinski, Ivan Zhou, Irene Dea, Krista Opsahl-Ong, Simon Favreau-Lessard, Sean Owen, Jose Javier Gonzalez Ortiz, Arnav Singhvi, Xabi Andrade, Cindy Wang, Kartik Sreenivasan, Sam Havens, Jialu Liu, Peyton DeNiro, Wen Sun, Michael Bendersky, Jonathan Frankle
2026	J	`jnl`	LLMs Can Learn to Reason Via Off-Policy RL. CoRR Daniel Ritter, Owen Oertell, Bradley Guo, Jonathan D. Chang, Kianté Brantley, Wen Sun
2025	A*	`conf`	A Reductions Approach to Risk-Sensitive Reinforcement Learning with Optimized Certainty Equivalents. ICML Kaiwen Wang, Dawen Liang, Nathan Kallus, Wen Sun
2025	J	`jnl`	Accelerating RL for LLM Reasoning with Optimal Advantage Regression. CoRR Kianté Brantley, Mingyu Chen, Zhaolin Gao, Jason D. Lee, Wen Sun, Wenhao Zhan, Xuezhou Zhang
2025	J	`jnl`	All Roads Lead to Likelihood: The Value of Reinforcement Learning in Fine-Tuning. CoRR Gokul Swamy, Sanjiban Choudhury, Wen Sun, Zhiwei Steven Wu, J. Andrew Bagnell
2025	A*	`conf`	Computationally Efficient RL under Linear Bellman Completeness for Deterministic Dynamics. ICLR Runzhe Wu, Ayush Sekhari, Akshay Krishnamurthy, Wen Sun
2025	J	`jnl`	Convergence Of Consistency Model With Multistep Sampling Under General Data Assumptions. CoRR Yiding Chen, Yiyi Zhang, Owen Oertell, Wen Sun
2025	A*	`conf`	Convergence of Consistency Model with Multistep Sampling under General Data Assumptions. ICML Yiding Chen, Yiyi Zhang, Owen Oertell, Wen Sun
2025	A*	`conf`	Correcting the Mythos of KL-Regularization: Direct Alignment without Overoptimization via Chi-Squared Preference Optimization. ICLR Audrey Huang, Wenhao Zhan, Tengyang Xie, Jason D. Lee, Wen Sun, Akshay Krishnamurthy, Dylan J. Foster
2025	J	`jnl`	Corruption-Robust Exploration in Episodic Reinforcement Learning. Math. Oper. Res. Thodoris Lykouris, Max Simchowitz, Aleksandrs Slivkins, Wen Sun
2025	A*	`conf`	Diffusing States and Matching Scores: A New Framework for Imitation Learning. ICLR Runzhe Wu, Yiding Chen, Gokul Swamy, Kianté Brantley, Wen Sun
2025	J	`jnl`	Efficient Controllable Diffusion via Optimal Classifier Guidance. CoRR Owen Oertell, Shikun Sun, Yiding Chen, Jin Peng Zhou, Zhiyong Wang, Wen Sun
2025	A*	`conf`	Efficient Imitation under Misspecification. ICLR Nicolas A. Espinosa Dice, Sanjiban Choudhury, Wen Sun, Gokul Swamy
2025	J	`jnl`	Efficient Imitation under Misspecification. CoRR Nicolas A. Espinosa Dice, Sanjiban Choudhury, Wen Sun, Gokul Swamy
2025	J	`jnl`	Expressive Value Learning for Scalable Offline Reinforcement Learning. CoRR Nicolas A. Espinosa Dice, Kianté Brantley, Wen Sun
2025	A*	`conf`	Model-based RL as a Minimalist Approach to Horizon-Free and Second-Order Bounds. ICLR Zhiyong Wang, Dongruo Zhou, John C. S. Lui, Wen Sun
2025	A*	`conf`	On Speeding Up Language Model Evaluation. ICLR Jin Peng Zhou, Christian K. Belardi, Ruihan Wu, Travis Zhang, Carla P. Gomes, Wen Sun, Kilian Q. Weinberger
2025	J	`jnl`	Prompt Curriculum Learning for Efficient LLM Post-Training. CoRR Zhaolin Gao, Joongwon Kim, Wen Sun, Thorsten Joachims, Sid Wang, Richard Yuanzhe Pang, Liang Tan
2025	J	`jnl`	Q♯: Provably Optimal Distributional RL for LLM Post-Training. CoRR Jin Peng Zhou, Kaiwen Wang, Jonathan D. Chang, Zhaolin Gao, Nathan Kallus, Kilian Q. Weinberger, Kianté Brantley, Wen Sun
2025	A*	`conf`	Regressing the Relative Future: Efficient Policy Optimization for Multi-turn RLHF. ICLR Zhaolin Gao, Wenhao Zhan, Jonathan Daniel Chang, Gokul Swamy, Kianté Brantley, Jason D. Lee, Wen Sun
2025	J	`jnl`	Scaling Offline RL via Efficient and Expressive Shortcut Models. CoRR Nicolas A. Espinosa Dice, Yiyi Zhang, Yiding Chen, Bradley Guo, Owen Oertell, Gokul Swamy, Kianté Brantley, Wen Sun
2025	J	`jnl`	Value-Guided Search for Efficient Chain-of-Thought Reasoning. CoRR Kaiwen Wang, Jin Peng Zhou, Jonathan D. Chang, Zhaolin Gao, Nathan Kallus, Kianté Brantley, Wen Sun
2024	A*	`conf`	Adversarial Imitation Learning via Boosting. ICLR Jonathan D. Chang, Dhruv Sreenivas, Yingbing Huang, Kianté Brantley, Wen Sun
2024	J	`jnl`	Adversarial Imitation Learning via Boosting. CoRR Jonathan D. Chang, Dhruv Sreenivas, Yingbing Huang, Kianté Brantley, Wen Sun
2024	J	`jnl`	Computationally Efficient RL under Linear Bellman Completeness for Deterministic Dynamics. CoRR Runzhe Wu, Ayush Sekhari, Akshay Krishnamurthy, Wen Sun
2024	J	`jnl`	Correcting the Mythos of KL-Regularization: Direct Alignment without Overoptimization via Chi-Squared Preference Optimization. CoRR Audrey Huang, Wenhao Zhan, Tengyang Xie, Jason D. Lee, Wen Sun, Akshay Krishnamurthy, Dylan J. Foster
2024	J	`jnl`	Dataset Reset Policy Optimization for RLHF. CoRR Jonathan D. Chang, Wenhao Zhan, Owen Oertell, Kianté Brantley, Dipendra Misra, Jason D. Lee, Wen Sun
2024	J	`jnl`	Diffusing States and Matching Scores: A New Framework for Imitation Learning. CoRR Runzhe Wu, Yiding Chen, Gokul Swamy, Kianté Brantley, Wen Sun
2024	A*	`conf`	Efficient and Sharp Off-Policy Evaluation in Robust Markov Decision Processes. NeurIPS Andrew Bennett, Nathan Kallus, Miruna Oprescu, Wen Sun, Kaiwen Wang
2024	J	`jnl`	Efficient and Sharp Off-Policy Evaluation in Robust Markov Decision Processes. CoRR Andrew Bennett, Nathan Kallus, Miruna Oprescu, Wen Sun, Kaiwen Wang
2024	J	`jnl`	JoinGym: An Efficient Join Order Selection Environment. RLJ Junxiong Wang, Kaiwen Wang, Yueying Li, Nathan Kallus, Immanuel Trummer, Wen Sun
2024	A*	`conf`	Making RL with Preference-based Feedback Efficient via Randomization. ICLR Runzhe Wu, Wen Sun
2024	J	`jnl`	Model-based RL as a Minimalist Approach to Horizon-Free and Second-Order Bounds. CoRR Zhiyong Wang, Dongruo Zhou, John C. S. Lui, Wen Sun
2024	A*	`conf`	More Benefits of Being Distributional: Second-Order Bounds for Reinforcement Learning. ICML Kaiwen Wang, Owen Oertell, Alekh Agarwal, Nathan Kallus, Wen Sun
2024	J	`jnl`	More Benefits of Being Distributional: Second-Order Bounds for Reinforcement Learning. CoRR Kaiwen Wang, Owen Oertell, Alekh Agarwal, Nathan Kallus, Wen Sun
2024	A*	`conf`	Offline Data Enhanced On-Policy Policy Gradient with Provable Guarantees. ICLR Yifei Zhou, Ayush Sekhari, Yuda Song, Wen Sun
2024	J	`jnl`	On Speeding Up Language Model Evaluation. CoRR Jin Peng Zhou, Christian K. Belardi, Ruihan Wu, Travis Zhang, Carla P. Gomes, Wen Sun, Kilian Q. Weinberger
2024	J	`jnl`	Orchestrating LLMs with Different Personalizations. CoRR Jin Peng Zhou, Katie Z. Luo, Jingwen Gu, Jason Yuan, Kilian Q. Weinberger, Wen Sun
2024	A*	`conf`	Provable Offline Preference-Based Reinforcement Learning. ICLR Wenhao Zhan, Masatoshi Uehara, Nathan Kallus, Jason D. Lee, Wen Sun
2024	A*	`conf`	Provable Reward-Agnostic Preference-Based Reinforcement Learning. ICLR Wenhao Zhan, Masatoshi Uehara, Wen Sun, Jason D. Lee
2024	A*	`conf`	Provably Efficient CVaR RL in Low-rank MDPs. ICLR Yulai Zhao, Wenhao Zhan, Xiaoyan Hu, Ho-fung Leung, Farzan Farnia, Wen Sun, Jason D. Lee
2024	A*	`conf`	REBEL: Reinforcement Learning via Regressing Relative Rewards. NeurIPS Zhaolin Gao, Jonathan D. Chang, Wenhao Zhan, Owen Oertell, Gokul Swamy, Kianté Brantley, Thorsten Joachims, Drew Bagnell, Jason D. Lee, Wen Sun
2024	J	`jnl`	REBEL: Reinforcement Learning via Regressing Relative Rewards. CoRR Zhaolin Gao, Jonathan D. Chang, Wenhao Zhan, Owen Oertell, Gokul Swamy, Kianté Brantley, Thorsten Joachims, J. Andrew Bagnell, Jason D. Lee, Wen Sun
2024	J	`jnl`	RL for Consistency Models: Faster Reward Guided Text-to-Image Generation. CoRR Owen Oertell, Jonathan D. Chang, Yiyi Zhang, Kianté Brantley, Wen Sun
2024	J	`jnl`	RL for Consistency Models: Reward Guided Text-to-Image Generation with Fast Inference. RLJ Owen Oertell, Jonathan D. Chang, Yiyi Zhang, Kianté Brantley, Wen Sun
2024	J	`jnl`	Regressing the Relative Future: Efficient Policy Optimization for Multi-turn RLHF. CoRR Zhaolin Gao, Wenhao Zhan, Jonathan D. Chang, Gokul Swamy, Kianté Brantley, Jason D. Lee, Wen Sun
2024	J	`jnl`	Risk-Sensitive RL with Optimized Certainty Equivalents via Reduction to Standard RL. CoRR Kaiwen Wang, Dawen Liang, Nathan Kallus, Wen Sun
2024	J	`jnl`	The Central Role of the Loss Function in Reinforcement Learning. CoRR Kaiwen Wang, Nathan Kallus, Wen Sun
2024	A*	`conf`	The Importance of Online Data: Understanding Preference Fine-tuning via Coverage. NeurIPS Yuda Song, Gokul Swamy, Aarti Singh, J. Andrew Bagnell, Wen Sun
2024	J	`jnl`	Understanding Preference Fine-Tuning Through the Lens of Coverage. CoRR Yuda Song, Gokul Swamy, Aarti Singh, J. Andrew Bagnell, Wen Sun
2023	A*	`conf`	Computationally Efficient PAC RL in POMDPs with Latent Determinism and Conditional Embeddings. ICML Masatoshi Uehara, Ayush Sekhari, Jason D. Lee, Nathan Kallus, Wen Sun
2023	J	`jnl`	Contextual Bandits and Imitation Learning via Preference-Based Active Queries. CoRR Ayush Sekhari, Karthik Sridharan, Wen Sun, Runzhe Wu
2023	A*	`conf`	Contextual Bandits and Imitation Learning with Preference-Based Active Queries. NeurIPS Ayush Sekhari, Karthik Sridharan, Wen Sun, Runzhe Wu
2023	A*	`conf`	Distributional Offline Policy Evaluation with Predictive Error Guarantees. ICML Runzhe Wu, Masatoshi Uehara, Wen Sun
2023	J	`jnl`	Distributional Offline Policy Evaluation with Predictive Error Guarantees. CoRR Runzhe Wu, Masatoshi Uehara, Wen Sun
2023	A*	`conf`	Future-Dependent Value-Based Off-Policy Evaluation in POMDPs. NeurIPS Masatoshi Uehara, Haruka Kiyohara, Andrew Bennett, Victor Chernozhukov, Nan Jiang, Nathan Kallus, Chengchun Shi, Wen Sun
2023	J	`jnl`	How to Query Human Feedback Efficiently in RL? CoRR Wenhao Zhan, Masatoshi Uehara, Wen Sun, Jason D. Lee
2023	A*	`conf`	Hybrid RL: Using both offline and online data can make RL efficient. ICLR Yuda Song, Yifei Zhou, Ayush Sekhari, Drew Bagnell, Akshay Krishnamurthy, Wen Sun
2023	J	`jnl`	JoinGym: An Efficient Query Optimization Environment for Reinforcement Learning. CoRR Kaiwen Wang, Junxiong Wang, Yueying Li, Nathan Kallus, Immanuel Trummer, Wen Sun
2023	J	`jnl`	Learning to Generate Better Than Your LLM. CoRR Jonathan D. Chang, Kianté Brantley, Rajkumar Ramamurthy, Dipendra Misra, Wen Sun
2023	J	`jnl`	Making RL with Preference-based Feedback Efficient via Randomization. CoRR Runzhe Wu, Wen Sun
2023	A*	`conf`	Near-Minimax-Optimal Risk-Sensitive Reinforcement Learning with CVaR. ICML Kaiwen Wang, Nathan Kallus, Wen Sun
2023	J	`jnl`	Near-Minimax-Optimal Risk-Sensitive Reinforcement Learning with CVaR. CoRR Kaiwen Wang, Nathan Kallus, Wen Sun
2023	J	`jnl`	Offline Data Enhanced On-Policy Policy Gradient with Provable Guarantees. CoRR Yifei Zhou, Ayush Sekhari, Yuda Song, Wen Sun
2023	A*	`conf`	Offline Minimax Soft-Q-learning Under Realizability and Partial Coverage. NeurIPS Masatoshi Uehara, Nathan Kallus, Jason D. Lee, Wen Sun
2023	A*	`conf`	PAC Reinforcement Learning for Predictive State Representations. ICLR Wenhao Zhan, Masatoshi Uehara, Wen Sun, Jason D. Lee
2023	A*	`conf`	Provable Benefits of Representational Transfer in Reinforcement Learning. COLT Alekh Agarwal, Yuda Song, Wen Sun, Kaiwen Wang, Mengdi Wang, Xuezhou Zhang
2023	J	`jnl`	Provable Offline Reinforcement Learning with Human Feedback. CoRR Wenhao Zhan, Masatoshi Uehara, Nathan Kallus, Jason D. Lee, Wen Sun
2023	J	`jnl`	Provably Efficient CVaR RL in Low-rank MDPs. CoRR Yulai Zhao, Wenhao Zhan, Xiaoyan Hu, Ho-fung Leung, Farzan Farnia, Wen Sun, Jason D. Lee
2023	J	`jnl`	Refined Value-Based Offline RL under Realizability and Partial Coverage. CoRR Masatoshi Uehara, Nathan Kallus, Jason D. Lee, Wen Sun
2023	A*	`conf`	Reward Finetuning for Faster and More Accurate Unsupervised Object Discovery. NeurIPS Katie Luo, Zhenzhen Liu, Xiangyu Chen, Yurong You, Sagie Benaim, Cheng Perng Phoo, Mark E. Campbell, Wen Sun, Bharath Hariharan, Kilian Q. Weinberger
2023	J	`jnl`	Reward Finetuning for Faster and More Accurate Unsupervised Object Discovery. CoRR Katie Z. Luo, Zhenzhen Liu, Xiangyu Chen, Yurong You, Sagie Benaim, Cheng Perng Phoo, Mark E. Campbell, Wen Sun, Bharath Hariharan, Kilian Q. Weinberger
2023	A*	`conf`	Selective Sampling and Imitation Learning via Online Regression. NeurIPS Ayush Sekhari, Karthik Sridharan, Wen Sun, Runzhe Wu
2023	J	`jnl`	Selective Sampling and Imitation Learning via Online Regression. CoRR Ayush Sekhari, Karthik Sridharan, Wen Sun, Runzhe Wu
2023	A*	`conf`	The Benefits of Being Distributional: Small-Loss Bounds for Reinforcement Learning. NeurIPS Kaiwen Wang, Kevin Zhou, Runzhe Wu, Nathan Kallus, Wen Sun
2023	J	`jnl`	The Benefits of Being Distributional: Small-Loss Bounds for Reinforcement Learning. CoRR Kaiwen Wang, Kevin Zhou, Runzhe Wu, Nathan Kallus, Wen Sun
2022	J	`jnl`	Computationally Efficient PAC RL in POMDPs with Latent Determinism and Conditional Embeddings. CoRR Masatoshi Uehara, Ayush Sekhari, Jason D. Lee, Nathan Kallus, Wen Sun
2022	A	`conf`	Corruption-robust Offline Reinforcement Learning. AISTATS Xuezhou Zhang, Yiding Chen, Xiaojin Zhu, Wen Sun
2022	J	`jnl`	Efficient Reinforcement Learning in Block MDPs: A Model-free Representation Learning Approach. CoRR Xuezhou Zhang, Yuda Song, Masatoshi Uehara, Mengdi Wang, Alekh Agarwal, Wen Sun
2022	A*	`conf`	Efficient Reinforcement Learning in Block MDPs: A Model-free Representation Learning approach. ICML Xuezhou Zhang, Yuda Song, Masatoshi Uehara, Mengdi Wang, Alekh Agarwal, Wen Sun
2022	J	`jnl`	Future-Dependent Value-Based Off-Policy Evaluation in POMDPs. CoRR Masatoshi Uehara, Haruka Kiyohara, Andrew Bennett, Victor Chernozhukov, Nan Jiang, Nathan Kallus, Chengchun Shi, Wen Sun
2022	A*	`conf`	Hindsight is 20/20: Leveraging Past Traversals to Aid 3D Perception. ICLR Yurong You, Katie Z. Luo, Xiangyu Chen, Junan Chen, Wei-Lun Chao, Wen Sun, Bharath Hariharan, Mark E. Campbell, Kilian Q. Weinberger
2022	J	`jnl`	Hindsight is 20/20: Leveraging Past Traversals to Aid 3D Perception. CoRR Yurong You, Katie Z. Luo, Xiangyu Chen, Junan Chen, Wei-Lun Chao, Wen Sun, Bharath Hariharan, Mark E. Campbell, Kilian Q. Weinberger
2022	J	`jnl`	Hybrid RL: Using Both Offline and Online Data Can Make RL Efficient. CoRR Yuda Song, Yifei Zhou, Ayush Sekhari, J. Andrew Bagnell, Akshay Krishnamurthy, Wen Sun
2022	A*	`conf`	Learning Bellman Complete Representations for Offline Policy Evaluation. ICML Jonathan D. Chang, Kaiwen Wang, Nathan Kallus, Wen Sun
2022	J	`jnl`	Learning Bellman Complete Representations for Offline Policy Evaluation. CoRR Jonathan D. Chang, Kaiwen Wang, Nathan Kallus, Wen Sun
2022	A*	`conf`	Learning to Detect Mobile Objects from LiDAR Scans Without Labels. CVPR Yurong You, Katie Luo, Cheng Perng Phoo, Wei-Lun Chao, Wen Sun, Bharath Hariharan, Mark E. Campbell, Kilian Q. Weinberger
2022	J	`jnl`	Learning to Detect Mobile Objects from LiDAR Scans Without Labels. CoRR Yurong You, Katie Z. Luo, Cheng Perng Phoo, Wei-Lun Chao, Wen Sun, Bharath Hariharan, Mark E. Campbell, Kilian Q. Weinberger
2022	—	`conf`	On the Effectiveness of Iterative Learning Control. L4DC Anirudh Vemula, Wen Sun, Maxim Likhachev, J. Andrew Bagnell
2022	—	`conf`	Online No-regret Model-Based Meta RL for Personalized Navigation. L4DC Yuda Song, Ye Yuan, Wen Sun, Kris Kitani
2022	J	`jnl`	Online No-regret Model-Based Meta RL for Personalized Navigation. CoRR Yuda Song, Ye Yuan, Wen Sun, Kris Kitani
2022	J	`jnl`	PAC Reinforcement Learning for Predictive State Representations. CoRR Wenhao Zhan, Masatoshi Uehara, Wen Sun, Jason D. Lee
2022	A*	`conf`	Pessimistic Model-based Offline Reinforcement Learning under Partial Coverage. ICLR Masatoshi Uehara, Wen Sun
2022	J	`jnl`	Provable Benefits of Representational Transfer in Reinforcement Learning. CoRR Alekh Agarwal, Yuda Song, Wen Sun, Kaiwen Wang, Mengdi Wang, Xuezhou Zhang
2022	A*	`conf`	Provably Efficient Reinforcement Learning in Partially Observable Dynamical Systems. NeurIPS Masatoshi Uehara, Ayush Sekhari, Jason D. Lee, Nathan Kallus, Wen Sun
2022	J	`jnl`	Provably Efficient Reinforcement Learning in Partially Observable Dynamical Systems. CoRR Masatoshi Uehara, Ayush Sekhari, Jason D. Lee, Nathan Kallus, Wen Sun
2022	A*	`conf`	Representation Learning for Online and Offline RL in Low-rank MDPs. ICLR Masatoshi Uehara, Xuezhou Zhang, Wen Sun
2022	A*	`conf`	Transform2Act: Learning a Transform-and-Control Policy for Efficient Agent Design. ICLR Ye Yuan, Yuda Song, Zhengyi Luo, Wen Sun, Kris M. Kitani
2021	A*	`conf`	Bilinear Classes: A Structural Framework for Provable Generalization in RL. ICML Simon S. Du, Sham M. Kakade, Jason D. Lee, Shachar Lovett, Gaurav Mahajan, Wen Sun, Ruosong Wang
2021	J	`jnl`	Bilinear Classes: A Structural Framework for Provable Generalization in RL. CoRR Simon S. Du, Sham M. Kakade, Jason D. Lee, Shachar Lovett, Gaurav Mahajan, Wen Sun, Ruosong Wang
2021	J	`jnl`	Corruption-Robust Offline Reinforcement Learning. CoRR Xuezhou Zhang, Yiding Chen, Jerry Zhu, Wen Sun
2021	A*	`conf`	Corruption-robust exploration in episodic reinforcement learning. COLT Thodoris Lykouris, Max Simchowitz, Alex Slivkins, Wen Sun
2021	A*	`conf`	Fairness of Exposure in Stochastic Bandits. ICML Lequn Wang, Yiwei Bai, Wen Sun, Thorsten Joachims
2021	J	`jnl`	Fairness of Exposure in Stochastic Bandits. CoRR Lequn Wang, Yiwei Bai, Wen Sun, Thorsten Joachims
2021	J	`jnl`	Finite Sample Analysis of Minimax Offline Reinforcement Learning: Completeness, Fast Rates and First-Order Efficiency. CoRR Masatoshi Uehara, Masaaki Imaizumi, Nan Jiang, Nathan Kallus, Wen Sun, Tengyang Xie
2021	C	`conf`	Imitation Learning as f-Divergence Minimization. WAFR Liyiming Ke, Sanjiban Choudhury, Matt Barnes, Wen Sun, Gilwoo Lee, Siddhartha S. Srinivasa
2021	A*	`conf`	Mitigating Covariate Shift in Imitation Learning via Offline Data With Partial Coverage. NeurIPS Jonathan D. Chang, Masatoshi Uehara, Dhruv Sreenivas, Rahul Kidambi, Wen Sun
2021	J	`jnl`	Mitigating Covariate Shift in Imitation Learning via Offline Data Without Great Coverage. CoRR Jonathan D. Chang, Masatoshi Uehara, Dhruv Sreenivas, Rahul Kidambi, Wen Sun
2021	A*	`conf`	MobILE: Model-Based Imitation Learning From Observation Alone. NeurIPS Rahul Kidambi, Jonathan D. Chang, Wen Sun
2021	J	`jnl`	On the Effectiveness of Iterative Learning Control. CoRR Anirudh Vemula, Wen Sun, Maxim Likhachev, J. Andrew Bagnell
2021	J	`jnl`	Optimism is All You Need: Model-Based Imitation Learning From Observation Alone. CoRR Rahul Kidambi, Jonathan D. Chang, Wen Sun
2021	A*	`conf`	PC-MLP: Model-based Reinforcement Learning with Policy Cover Guided Exploration. ICML Yuda Song, Wen Sun
2021	J	`jnl`	PC-MLP: Model-based Reinforcement Learning with Policy Cover Guided Exploration. CoRR Yuda Song, Wen Sun
2021	J	`jnl`	Pessimistic Model-based Offline RL: PAC Bounds and Posterior Sampling under Partial Coverage. CoRR Masatoshi Uehara, Wen Sun
2021	J	`jnl`	Representation Learning for Online and Offline RL in Low-rank MDPs. CoRR Masatoshi Uehara, Xuezhou Zhang, Wen Sun
2021	A*	`conf`	Robust Policy Gradient against Strong Data Corruption. ICML Xuezhou Zhang, Yiding Chen, Xiaojin Zhu, Wen Sun
2021	J	`jnl`	Robust Policy Gradient against Strong Data Corruption. CoRR Xuezhou Zhang, Yiding Chen, Xiaojin Zhu, Wen Sun
2021	J	`jnl`	Transform2Act: Learning a Transform-and-Control Policy for Efficient Agent Design. CoRR Ye Yuan, Yuda Song, Zhengyi Luo, Wen Sun, Kris Kitani
2020	A*	`conf`	Constrained episodic reinforcement learning in concave-convex and knapsack settings. NeurIPS Kianté Brantley, Miroslav Dudík, Thodoris Lykouris, Sobhan Miryoosefi, Max Simchowitz, Aleksandrs Slivkins, Wen Sun
2020	J	`jnl`	Constrained episodic reinforcement learning in concave-convex and knapsack settings. CoRR Kianté Brantley, Miroslav Dudík, Thodoris Lykouris, Sobhan Miryoosefi, Max Simchowitz, Aleksandrs Slivkins, Wen Sun
2020	A*	`conf`	Disagreement-Regularized Imitation Learning. ICLR Kianté Brantley, Wen Sun, Mikael Henaff
2020	J	`jnl`	Exploration in Action Space. CoRR Anirudh Vemula, Wen Sun, J. Andrew Bagnell
2020	A*	`conf`	FLAMBE: Structural Complexity and Representation Learning of Low Rank MDPs. NeurIPS Alekh Agarwal, Sham M. Kakade, Akshay Krishnamurthy, Wen Sun
2020	J	`jnl`	FLAMBE: Structural Complexity and Representation Learning of Low Rank MDPs. CoRR Alekh Agarwal, Sham M. Kakade, Akshay Krishnamurthy, Wen Sun
2020	A*	`conf`	Information Theoretic Regret Bounds for Online Nonlinear Control. NeurIPS Sham M. Kakade, Akshay Krishnamurthy, Kendall Lowrey, Motoya Ohnishi, Wen Sun
2020	J	`jnl`	Information Theoretic Regret Bounds for Online Nonlinear Control. CoRR Sham M. Kakade, Akshay Krishnamurthy, Kendall Lowrey, Motoya Ohnishi, Wen Sun
2020	A*	`conf`	Learning the Linear Quadratic Regulator from Nonlinear Observations. NeurIPS Zakaria Mhammedi, Dylan J. Foster, Max Simchowitz, Dipendra Misra, Wen Sun, Akshay Krishnamurthy, Alexander Rakhlin, John Langford
2020	J	`jnl`	Learning the Linear Quadratic Regulator from Nonlinear Observations. CoRR Zakaria Mhammedi, Dylan J. Foster, Max Simchowitz, Dipendra Misra, Wen Sun, Akshay Krishnamurthy, Alexander Rakhlin, John Langford
2020	A*	`conf`	PC-PG: Policy Cover Directed Exploration for Provable Policy Gradient Learning. NeurIPS Alekh Agarwal, Mikael Henaff, Sham M. Kakade, Wen Sun
2020	J	`jnl`	PC-PG: Policy Cover Directed Exploration for Provable Policy Gradient Learning. CoRR Alekh Agarwal, Mikael Henaff, Sham M. Kakade, Wen Sun
2020	A*	`conf`	Provably Efficient Model-based Policy Adaptation. ICML Yuda Song, Aditi Mavalankar, Wen Sun, Sicun Gao
2020	J	`jnl`	Provably Efficient Model-based Policy Adaptation. CoRR Yuda Song, Aditi Mavalankar, Wen Sun, Sicun Gao
2019	A*	`conf`	Contextual Memory Trees. ICML Wen Sun, Alina Beygelzimer, Hal Daumé III, John Langford, Paul Mineiro
2019	A	`conf`	Contrasting Exploration in Parameter and Action Space: A Zeroth-Order Optimization Perspective. AISTATS Anirudh Vemula, Wen Sun, J. Andrew Bagnell
2019	J	`jnl`	Contrasting Exploration in Parameter and Action Space: A Zeroth-Order Optimization Perspective. CoRR Anirudh Vemula, Wen Sun, J. Andrew Bagnell
2019	J	`jnl`	Corruption Robust Exploration in Episodic Reinforcement Learning. CoRR Thodoris Lykouris, Max Simchowitz, Aleksandrs Slivkins, Wen Sun
2019	J	`jnl`	Imitation Learning as f-Divergence Minimization. CoRR Liyiming Ke, Matt Barnes, Wen Sun, Gilwoo Lee, Sanjiban Choudhury, Siddhartha S. Srinivasa
2019	A*	`conf`	Model-based RL in Contextual Decision Processes: PAC bounds and Exponential Improvements over Model-free Approaches. COLT Wen Sun, Nan Jiang, Akshay Krishnamurthy, Alekh Agarwal, John Langford
2019	A*	`conf`	Policy Poisoning in Batch Reinforcement Learning and Control. NeurIPS Yuzhe Ma, Xuezhou Zhang, Wen Sun, Jerry Zhu
2019	J	`jnl`	Policy Poisoning in Batch Reinforcement Learning and Control. CoRR Yuzhe Ma, Xuezhou Zhang, Wen Sun, Xiaojin Zhu
2019	A*	`conf`	Provably Efficient Imitation Learning from Observation Alone. ICML Wen Sun, Anirudh Vemula, Byron Boots, Drew Bagnell
2019	J	`jnl`	Provably Efficient Imitation Learning from Observation Alone. CoRR Wen Sun, Anirudh Vemula, Byron Boots, J. Andrew Bagnell
2019	—	`—`	Towards Generalization and Efficiency in Reinforcement Learning. Wen Sun
2018	J	`jnl`	Contextual Memory Trees. CoRR Wen Sun, Alina Beygelzimer, Hal Daumé III, John Langford, Paul Mineiro
2018	A*	`conf`	Dual Policy Iteration. NeurIPS Wen Sun, Geoffrey J. Gordon, Byron Boots, J. Andrew Bagnell
2018	J	`jnl`	Dual Policy Iteration. CoRR Wen Sun, Geoffrey J. Gordon, Byron Boots, J. Andrew Bagnell
2018	J	`jnl`	Model-Based Reinforcement Learning in Contextual Decision Processes. CoRR Wen Sun, Nan Jiang, Akshay Krishnamurthy, Alekh Agarwal, John Langford
2018	A*	`conf`	Recurrent Predictive State Policy Networks. ICML Ahmed Hefny, Zita Marinho, Wen Sun, Siddhartha S. Srinivasa, Geoffrey J. Gordon
2018	J	`jnl`	Recurrent Predictive State Policy Networks. CoRR Ahmed Hefny, Zita Marinho, Wen Sun, Siddhartha S. Srinivasa, Geoffrey J. Gordon
2018	J	`jnl`	Truncated Horizon Policy Search: Combining Reinforcement Learning & Imitation Learning. CoRR Wen Sun, J. Andrew Bagnell, Byron Boots
2018	—	`conf`	Truncated horizon Policy Search: Combining Reinforcement Learning & Imitation Learning. ICLR (Poster) Wen Sun, J. Andrew Bagnell, Byron Boots
2017	A*	`conf`	Deeply AggreVaTeD: Differentiable Imitation Learning for Sequential Prediction. ICML Wen Sun, Arun Venkatraman, Geoffrey J. Gordon, Byron Boots, J. Andrew Bagnell
2017	J	`jnl`	Deeply AggreVaTeD: Differentiable Imitation Learning for Sequential Prediction. CoRR Wen Sun, Arun Venkatraman, Geoffrey J. Gordon, Byron Boots, J. Andrew Bagnell
2017	A	`conf`	Gradient Boosting on Stochastic Data Streams. AISTATS Hanzhang Hu, Wen Sun, Arun Venkatraman, Martial Hebert, J. Andrew Bagnell
2017	J	`jnl`	Gradient Boosting on Stochastic Data Streams. CoRR Hanzhang Hu, Wen Sun, Arun Venkatraman, Martial Hebert, J. Andrew Bagnell
2017	—	`conf`	Predictive-State Decoders: Encoding the Future into Recurrent Networks. NIPS Arun Venkatraman, Nicholas Rhinehart, Wen Sun, Lerrel Pinto, Martial Hebert, Byron Boots, Kris M. Kitani, James Andrew Bagnell
2017	J	`jnl`	Predictive-State Decoders: Encoding the Future into Recurrent Networks. CoRR Arun Venkatraman, Nicholas Rhinehart, Wen Sun, Lerrel Pinto, Martial Hebert, Byron Boots, Kris M. Kitani, J. Andrew Bagnell
2016	A*	`conf`	Inference Machines for Nonparametric Filter Learning. IJCAI Arun Venkatraman, Wen Sun, Martial Hebert, Byron Boots, J. Andrew Bagnell
2016	A*	`conf`	Learning to Filter with Predictive State Inference Machines. ICML Wen Sun, Arun Venkatraman, Byron Boots, J. Andrew Bagnell
2016	A	`conf`	Learning to Smooth with Bidirectional Predictive State Inference Machines. UAI Wen Sun, Roberto Capobianco, Geoffrey J. Gordon, J. Andrew Bagnell, Byron Boots
2016	A*	`conf`	Online Bellman Residual and Temporal Difference Algorithms with Predictive Error Guarantees. IJCAI Wen Sun, J. Andrew Bagnell
2016	A*	`conf`	Online Instrumental Variable Regression with Applications to Online Linear System Identification. AAAI Arun Venkatraman, Wen Sun, Martial Hebert, J. Andrew Bagnell, Byron Boots
2016	J	`jnl`	Stochastic Extended LQR for Optimization-Based Motion Planning Under Uncertainty. IEEE Trans Autom. Sci. Eng. Wen Sun, Jur van den Berg, Ron Alterovitz
2015	J	`jnl`	High-Frequency Replanning Under Uncertainty Using Parallel Sampling-Based Motion Planning. IEEE Trans. Robotics Wen Sun, Sachin Patil, Ron Alterovitz
2015	J	`jnl`	Learning to Filter with Predictive State Inference Machines. CoRR Wen Sun, Arun Venkatraman, Byron Boots, J. Andrew Bagnell
2015	A	`conf`	Online Bellman Residual Algorithms with Predictive Error Guarantees. UAI Wen Sun, J. Andrew Bagnell
2014	A*	`conf`	Motion planning for paramagnetic microparticles under motion and sensing uncertainty. ICRA Wen Sun, Islam S. M. Khalil, Sarthak Misra, Ron Alterovitz
2014	A	`conf`	Motion planning under uncertainty for medical needle steering using optimization in belief space. IROS Wen Sun, Ron Alterovitz
2014	C	`conf`	Stochastic Extended LQR: Optimization-Based Motion Planning Under Uncertainty. WAFR Wen Sun, Jur van den Berg, Ron Alterovitz
2013	C	`conf`	Safe Motion Planning for Imprecise Robotic Manipulators by Minimizing Probability of Collision. ISRR Wen Sun, Luis G. Torres, Jur van den Berg, Ron Alterovitz