Wen Sun

Model-based RL as a Minimalist Approach to Horizon-Free and Second-Order Bounds ICLR 2025 Diffusing States and Matching Scores: A New Framework for Imitation Learning ICLR 2025 A Reductions Approach to Risk-Sensitive Reinforcement Learning with Optimized Certainty Equivalents ICML 2025 Efficient Imitation under Misspecification ICLR 2025 On Speeding Up Language Model Evaluation ICLR 2025 Computationally Efficient RL under Linear Bellman Completeness for Deterministic Dynamics ICLR 2025 Regressing the Relative Future: Efficient Policy Optimization for Multi-turn RLHF ICLR 2025 SDGO: Self-Discrimination-Guided Optimization for Consistent Safety in Large Language Models EMNLP 2025 Convergence of Consistency Model with Multistep Sampling under General Data Assumptions ICML 2025 Correcting the Mythos of KL-Regularization: Direct Alignment without Overoptimization via Chi-Squared Preference Optimization ICLR 2025 Offline Data Enhanced On-Policy Policy Gradient with Provable Guarantees ICLR 2024 Making RL with Preference-based Feedback Efficient via Randomization ICLR 2024 Adversarial Imitation Learning via Boosting ICLR 2024 The Importance of Online Data: Understanding Preference Fine-tuning via Coverage NIPS 2024 REBEL: Reinforcement Learning via Regressing Relative Rewards NIPS 2024 Efficient and Sharp Off-Policy Evaluation in Robust Markov Decision Processes NIPS 2024 Faster Recalibration of an Online Predictor via Approachability AISTATS 2024 Provably Efficient CVaR RL in Low-rank MDPs ICLR 2024 Provable Reward-Agnostic Preference-Based Reinforcement Learning ICLR 2024 More Benefits of Being Distributional: Second-Order Bounds for Reinforcement Learning ICML 2024 Provable Offline Preference-Based Reinforcement Learning ICLR 2024 Distributional Offline Policy Evaluation with Predictive Error Guarantees ICML 2023 Hybrid RL: Using both offline and online data can make RL efficient ICLR 2023 PAC Reinforcement Learning for Predictive State Representations ICLR 2023 Multi-task Representation Learning for Pure Exploration in Linear Bandits ICML 2023 Computationally Efficient PAC RL in POMDPs with Latent Determinism and Conditional Embeddings ICML 2023 The Benefits of Being Distributional: Small-Loss Bounds for Reinforcement Learning NIPS 2023 Contextual Bandits and Imitation Learning with Preference-Based Active Queries NIPS 2023 Offline Minimax Soft-Q-learning Under Realizability and Partial Coverage NIPS 2023 Reward Finetuning for Faster and More Accurate Unsupervised Object Discovery NIPS 2023 Future-Dependent Value-Based Off-Policy Evaluation in POMDPs NIPS 2023 Selective Sampling and Imitation Learning via Online Regression NIPS 2023 Provable Benefits of Representational Transfer in Reinforcement Learning COLT 2023 Near-Minimax-Optimal Risk-Sensitive Reinforcement Learning with CVaR ICML 2023 Online No-regret Model-Based Meta RL for Personalized Navigation L4DC 2022 Provably Efficient Reinforcement Learning in Partially Observable Dynamical Systems NIPS 2022 Corruption-robust Offline Reinforcement Learning AISTATS 2022 Learning To Detect Mobile Objects From LiDAR Scans Without Labels CVPR 2022 Visual Named Entity Linking: A New Dataset and A Baseline EMNLP 2022 Pessimistic Model-based Offline Reinforcement Learning under Partial Coverage ICLR 2022 Hindsight is 20/20: Leveraging Past Traversals to Aid 3D Perception ICLR 2022 Transform2Act: Learning a Transform-and-Control Policy for Efficient Agent Design ICLR 2022 Representation Learning for Online and Offline RL in Low-rank MDPs ICLR 2022 Learning Bellman Complete Representations for Offline Policy Evaluation ICML 2022 Efficient Reinforcement Learning in Block MDPs: A Model-free Representation Learning approach ICML 2022 On the Effectiveness of Iterative Learning Control L4DC 2022 Corruption-robust exploration in episodic reinforcement learning COLT 2021 MobILE: Model-Based Imitation Learning From Observation Alone NIPS 2021 Mitigating Covariate Shift in Imitation Learning via Offline Data With Partial Coverage NIPS 2021 Bilinear Classes: A Structural Framework for Provable Generalization in RL ICML 2021 PC-MLP: Model-based Reinforcement Learning with Policy Cover Guided Exploration ICML 2021 Fairness of Exposure in Stochastic Bandits ICML 2021 Robust Policy Gradient against Strong Data Corruption ICML 2021 Constrained episodic reinforcement learning in concave-convex and knapsack settings NIPS 2020 Provably Efficient Model-based Policy Adaptation ICML 2020 Disagreement-Regularized Imitation Learning ICLR 2020 Information Theoretic Regret Bounds for Online Nonlinear Control NIPS 2020 Learning the Linear Quadratic Regulator from Nonlinear Observations NIPS 2020 PC-PG: Policy Cover Directed Exploration for Provable Policy Gradient Learning NIPS 2020 Multi-Robot Collision Avoidance under Uncertainty with Probabilistic Safety Barrier Certificates NIPS 2020 FLAMBE: Structural Complexity and Representation Learning of Low Rank MDPs NIPS 2020 Provably Efficient Imitation Learning from Observation Alone ICML 2019 Contrasting Exploration in Parameter and Action Space: A Zeroth-Order Optimization Perspective AISTATS 2019 Optimal Sketching for Kronecker Product Regression and Low Rank Approximation NIPS 2019 Model-based RL in Contextual Decision Processes: PAC bounds and Exponential Improvements over Model-free Approaches COLT 2019 Contextual Memory Trees ICML 2019 Policy Poisoning in Batch Reinforcement Learning and Control NIPS 2019 Recurrent Predictive State Policy Networks ICML 2018 Sketching for Kronecker Product Regression and P-splines AISTATS 2018 Dual Policy Iteration NIPS 2018 TRUNCATED HORIZON POLICY SEARCH: COMBINING REINFORCEMENT LEARNING & IMITATION LEARNING ICLR 2018 Predictive-State Decoders: Encoding the Future into Recurrent Networks NIPS 2017 The Frequency Range of “The Ling Six Sounds” in Standard Chinese INTERSPEECH 2017 Safety-Aware Algorithms for Adversarial Contextual Bandit ICML 2017 Deeply AggreVaTeD: Differentiable Imitation Learning for Sequential Prediction ICML 2017 Gradient Boosting on Stochastic Data Streams AISTATS 2017 Inference Machines for Nonparametric Filter Learning IJCAI 2016 Online Bellman Residual and Temporal Difference Algorithms with Predictive Error Guarantees IJCAI 2016 Learning to Filter with Predictive State Inference Machines ICML 2016