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ORCIDZhaoran Wang 0001
Person information
- affiliation: Northwestern University, Evanston, IL, USA
Other persons with the same name
- Zhaoran Wang 0002
![[0009-0005-2961-7324]](https://dblp1.uni-trier.de/img/orcid-mark.12x12.png "0009-0005-2961-7324")
— Inner Mongolia University, Hohhot, China - Zhaoran Wang 0003 — Tsinghua University, Beijing, China
- Zhaoran Wang 0004 — Shanghai University, School of Mechatronic Engineering and Automation, China
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2020 – today
- 2024
[j19]Xiao-Yang Liu, Ziyi Xia, Hongyang Yang, Jiechao Gao, Daochen Zha, Ming Zhu, Christina Dan Wang, Zhaoran Wang, Jian Guo:
Dynamic datasets and market environments for financial reinforcement learning. Mach. Learn. 113(5): 2795-2839 (2024)- [j18]Qi Cai, Zhuoran Yang, Jason D. Lee, Zhaoran Wang:
Neural Temporal Difference and Q Learning Provably Converge to Global Optima. Math. Oper. Res. 49(1): 619-651 (2024) - [j17]Zhihong Deng, Zuyue Fu, Lingxiao Wang, Zhuoran Yang, Chenjia Bai, Tianyi Zhou, Zhaoran Wang, Jing Jiang:
False Correlation Reduction for Offline Reinforcement Learning. IEEE Trans. Pattern Anal. Mach. Intell. 46(2): 1199-1211 (2024) - [j16]Chenjia Bai, Ting Xiao, Zhoufan Zhu, Lingxiao Wang, Fan Zhou, Animesh Garg, Bin He, Peng Liu, Zhaoran Wang:
Monotonic Quantile Network for Worst-Case Offline Reinforcement Learning. IEEE Trans. Neural Networks Learn. Syst. 35(7): 8954-8968 (2024) - [c129]Chau Pham, Boyi Liu, Yingxiang Yang, Zhengyu Chen, Tianyi Liu, Jianbo Yuan, Bryan A. Plummer, Zhaoran Wang, Hongxia Yang:
Let Models Speak Ciphers: Multiagent Debate through Embeddings. ICLR 2024 - [c128]Nuoya Xiong, Zhihan Liu, Zhaoran Wang, Zhuoran Yang:
Sample-Efficient Multi-Agent RL: An Optimization Perspective. ICLR 2024 - [c127]Feng Gao, Liangzhi Shi, Shenao Zhang, Zhaoran Wang, Yi Wu:
Adaptive-Gradient Policy Optimization: Enhancing Policy Learning in Non-Smooth Differentiable Simulations. ICML 2024 - [c126]Zhihan Liu, Hao Hu, Shenao Zhang, Hongyi Guo, Shuqi Ke, Boyi Liu, Zhaoran Wang:
Reason for Future, Act for Now: A Principled Architecture for Autonomous LLM Agents. ICML 2024 - [c125]Nuoya Xiong, Zhaoran Wang, Zhuoran Yang:
A General Framework for Sequential Decision-Making under Adaptivity Constraints. ICML 2024 - [c124]Sirui Zheng, Chenjia Bai, Zhuoran Yang, Zhaoran Wang:
How Does Goal Relabeling Improve Sample Efficiency? ICML 2024 - [i145]Hongyi Guo, Yuanshun Yao, Wei Shen, Jiaheng Wei, Xiaoying Zhang, Zhaoran Wang, Yang Liu:
Human-Instruction-Free LLM Self-Alignment with Limited Samples. CoRR abs/2401.06785 (2024) - [i144]Zihao Li, Boyi Liu, Zhuoran Yang, Zhaoran Wang, Mengdi Wang:
Double Duality: Variational Primal-Dual Policy Optimization for Constrained Reinforcement Learning. CoRR abs/2402.10810 (2024) - [i143]Shenao Zhang, Sirui Zheng, Shuqi Ke, Zhihan Liu, Wanxin Jin, Jianbo Yuan, Yingxiang Yang, Hongxia Yang, Zhaoran Wang:
How Can LLM Guide RL? A Value-Based Approach. CoRR abs/2402.16181 (2024) - [i142]Hongyi Guo, Zhihan Liu, Yufeng Zhang, Zhaoran Wang:
Can Large Language Models Play Games? A Case Study of A Self-Play Approach. CoRR abs/2403.05632 (2024) - [i141]Mengying Lin, Yaran Chen, Dongbin Zhao, Zhaoran Wang:
Advancing Object Goal Navigation Through LLM-enhanced Object Affinities Transfer. CoRR abs/2403.09971 (2024) - [i140]Yuchen Zhu, Yufeng Zhang, Zhaoran Wang, Zhuoran Yang, Xiaohong Chen:
A Mean-Field Analysis of Neural Gradient Descent-Ascent: Applications to Functional Conditional Moment Equations. CoRR abs/2404.12312 (2024) - [i139]Zhihan Liu, Miao Lu, Shenao Zhang, Boyi Liu, Hongyi Guo, Yingxiang Yang, Jose H. Blanchet, Zhaoran Wang:
Provably Mitigating Overoptimization in RLHF: Your SFT Loss is Implicitly an Adversarial Regularizer. CoRR abs/2405.16436 (2024) - [i138]Shenao Zhang, Donghan Yu, Hiteshi Sharma, Ziyi Yang, Shuohang Wang, Hany Hassan, Zhaoran Wang:
Self-Exploring Language Models: Active Preference Elicitation for Online Alignment. CoRR abs/2405.19332 (2024) - [i137]Rui Zheng, Hongyi Guo, Zhihan Liu, Xiaoying Zhang, Yuanshun Yao, Xiaojun Xu, Zhaoran Wang, Zhiheng Xi, Tao Gui, Qi Zhang, Xuanjing Huang, Hang Li, Yang Liu:
Toward Optimal LLM Alignments Using Two-Player Games. CoRR abs/2406.10977 (2024) - [i136]Zhixian Xie, Wenlong Zhang, Yi Ren, Zhaoran Wang, George J. Pappas, Wanxin Jin:
Safe MPC Alignment with Human Directional Feedback. CoRR abs/2407.04216 (2024) - 2023
- [j15]Han Zhong, Zhuoran Yang, Zhaoran Wang, Michael I. Jordan:
Can Reinforcement Learning Find Stackelberg-Nash Equilibria in General-Sum Markov Games with Myopically Rational Followers? J. Mach. Learn. Res. 24: 35:1-35:52 (2023) - [j14]Zihao Li, Boyi Liu, Zhuoran Yang, Zhaoran Wang, Mengdi Wang:
Double Duality: Variational Primal-Dual Policy Optimization for Constrained Reinforcement Learning. J. Mach. Learn. Res. 24: 385:1-385:43 (2023) - [j13]Qiaomin Xie, Yudong Chen, Zhaoran Wang, Zhuoran Yang:
Learning Zero-Sum Simultaneous-Move Markov Games Using Function Approximation and Correlated Equilibrium. Math. Oper. Res. 48(1): 433-462 (2023) - [j12]Chi Jin, Zhuoran Yang, Zhaoran Wang, Michael I. Jordan:
Provably Efficient Reinforcement Learning with Linear Function Approximation. Math. Oper. Res. 48(3): 1496-1521 (2023) - [j11]Mingyi Hong, Hoi-To Wai, Zhaoran Wang, Zhuoran Yang:
A Two-Timescale Stochastic Algorithm Framework for Bilevel Optimization: Complexity Analysis and Application to Actor-Critic. SIAM J. Optim. 33(1): 147-180 (2023) - [j10]Chenjia Bai, Lingxiao Wang, Yixin Wang, Zhaoran Wang, Rui Zhao, Chenyao Bai, Peng Liu:
Addressing Hindsight Bias in Multigoal Reinforcement Learning. IEEE Trans. Cybern. 53(1): 392-405 (2023) - [j9]Chenjia Bai, Peng Liu, Kaiyu Liu, Lingxiao Wang, Yingnan Zhao, Lei Han, Zhaoran Wang:
Variational Dynamic for Self-Supervised Exploration in Deep Reinforcement Learning. IEEE Trans. Neural Networks Learn. Syst. 34(8): 4776-4790 (2023) - [c123]Ruitu Xu, Yifei Min, Tianhao Wang, Michael I. Jordan, Zhaoran Wang, Zhuoran Yang:
Finding Regularized Competitive Equilibria of Heterogeneous Agent Macroeconomic Models via Reinforcement Learning. AISTATS 2023: 375-407 - [c122]Jing Wang, Meichen Song, Feng Gao, Boyi Liu, Zhaoran Wang, Yi Wu:
Differentiable Arbitrating in Zero-sum Markov Games. AAMAS 2023: 1034-1043 - [c121]Yixuan Wang, Simon Sinong Zhan, Zhilu Wang, Chao Huang, Zhaoran Wang, Zhuoran Yang, Qi Zhu:
Joint Differentiable Optimization and Verification for Certified Reinforcement Learning. ICCPS 2023: 132-141 - [c120]Lingxiao Wang, Qi Cai, Zhuoran Yang, Zhaoran Wang:
Represent to Control Partially Observed Systems: Representation Learning with Provable Sample Efficiency. ICLR 2023 - [c119]Miao Lu, Yifei Min, Zhaoran Wang, Zhuoran Yang:
Pessimism in the Face of Confounders: Provably Efficient Offline Reinforcement Learning in Partially Observable Markov Decision Processes. ICLR 2023 - [c118]Tongzheng Ren, Chenjun Xiao, Tianjun Zhang, Na Li, Zhaoran Wang, Sujay Sanghavi, Dale Schuurmans, Bo Dai:
Latent Variable Representation for Reinforcement Learning. ICLR 2023 - [c117]Haoran Xu, Li Jiang, Jianxiong Li, Zhuoran Yang, Zhaoran Wang, Wai Kin Victor Chan, Xianyuan Zhan:
Offline RL with No OOD Actions: In-Sample Learning via Implicit Value Regularization. ICLR 2023 - [c116]Sirui Zheng, Lingxiao Wang, Shuang Qiu, Zuyue Fu, Zhuoran Yang, Csaba Szepesvári, Zhaoran Wang:
Optimistic Exploration with Learned Features Provably Solves Markov Decision Processes with Neural Dynamics. ICLR 2023 - [c115]Jiayang Li, Jing Yu, Boyi Liu, Yu Nie, Zhaoran Wang:
Achieving Hierarchy-Free Approximation for Bilevel Programs with Equilibrium Constraints. ICML 2023: 20312-20335 - [c114]Yixuan Wang, Simon Sinong Zhan, Ruochen Jiao, Zhilu Wang, Wanxin Jin, Zhuoran Yang, Zhaoran Wang, Chao Huang, Qi Zhu:
Enforcing Hard Constraints with Soft Barriers: Safe Reinforcement Learning in Unknown Stochastic Environments. ICML 2023: 36593-36604 - [c113]Shenao Zhang, Wanxin Jin, Zhaoran Wang:
Adaptive Barrier Smoothing for First-Order Policy Gradient with Contact Dynamics. ICML 2023: 41219-41243 - [c112]Yulai Zhao, Zhuoran Yang, Zhaoran Wang, Jason D. Lee:
Local Optimization Achieves Global Optimality in Multi-Agent Reinforcement Learning. ICML 2023: 42200-42226 - [c111]Dongsheng Ding, Xiaohan Wei, Zhuoran Yang, Zhaoran Wang, Mihailo R. Jovanovic:
Provably Efficient Generalized Lagrangian Policy Optimization for Safe Multi-Agent Reinforcement Learning. L4DC 2023: 315-332 - [c110]Zhihan Liu, Miao Lu, Wei Xiong, Han Zhong, Hao Hu, Shenao Zhang, Sirui Zheng, Zhuoran Yang, Zhaoran Wang:
Maximize to Explore: One Objective Function Fusing Estimation, Planning, and Exploration. NeurIPS 2023 - [c109]Shuang Qiu, Ziyu Dai, Han Zhong, Zhaoran Wang, Zhuoran Yang, Tong Zhang:
Posterior Sampling for Competitive RL: Function Approximation and Partial Observation. NeurIPS 2023 - [c108]Shenao Zhang, Boyi Liu, Zhaoran Wang, Tuo Zhao:
Model-Based Reparameterization Policy Gradient Methods: Theory and Practical Algorithms. NeurIPS 2023 - [c107]Fengzhuo Zhang, Vincent Y. F. Tan, Zhaoran Wang, Zhuoran Yang:
Learning Regularized Monotone Graphon Mean-Field Games. NeurIPS 2023 - [i135]Jiayang Li, Jing Yu, Boyi Liu, Zhaoran Wang, Yu Marco Nie:
Achieving Hierarchy-Free Approximation for Bilevel Programs With Equilibrium Constraints. CoRR abs/2302.09734 (2023) - [i134]Jing Wang, Meichen Song, Feng Gao, Boyi Liu, Zhaoran Wang, Yi Wu:
Differentiable Arbitrating in Zero-sum Markov Games. CoRR abs/2302.10058 (2023) - [i133]Ruitu Xu, Yifei Min, Tianhao Wang, Zhaoran Wang, Michael I. Jordan, Zhuoran Yang:
Finding Regularized Competitive Equilibria of Heterogeneous Agent Macroeconomic Models with Reinforcement Learning. CoRR abs/2303.04833 (2023) - [i132]Siyu Chen, Yitan Wang, Zhaoran Wang, Zhuoran Yang:
A Unified Framework of Policy Learning for Contextual Bandit with Confounding Bias and Missing Observations. CoRR abs/2303.11187 (2023) - [i131]Haoran Xu, Li Jiang, Jianxiong Li, Zhuoran Yang, Zhaoran Wang, Wai Kin Victor Chan, Xianyuan Zhan:
Offline RL with No OOD Actions: In-Sample Learning via Implicit Value Regularization. CoRR abs/2303.15810 (2023) - [i130]Jiayang Li, Zhaoran Wang, Yu Marco Nie:
Wardrop Equilibrium Can Be Boundedly Rational: A New Behavioral Theory of Route Choice. CoRR abs/2304.02500 (2023) - [i129]Xiao-Yang Liu, Ziyi Xia, Hongyang Yang, Jiechao Gao, Daochen Zha, Ming Zhu, Christina Dan Wang, Zhaoran Wang, Jian Guo:
Dynamic Datasets and Market Environments for Financial Reinforcement Learning. CoRR abs/2304.13174 (2023) - [i128]Yulai Zhao, Zhuoran Yang, Zhaoran Wang, Jason D. Lee:
Local Optimization Achieves Global Optimality in Multi-Agent Reinforcement Learning. CoRR abs/2305.04819 (2023) - [i127]Zhihan Liu, Miao Lu, Wei Xiong, Han Zhong, Hao Hu, Shenao Zhang, Sirui Zheng, Zhuoran Yang, Zhaoran Wang:
One Objective to Rule Them All: A Maximization Objective Fusing Estimation and Planning for Exploration. CoRR abs/2305.18258 (2023) - [i126]Yufeng Zhang, Fengzhuo Zhang, Zhuoran Yang, Zhaoran Wang:
What and How does In-Context Learning Learn? Bayesian Model Averaging, Parameterization, and Generalization. CoRR abs/2305.19420 (2023) - [i125]Dongsheng Ding, Xiaohan Wei, Zhuoran Yang, Zhaoran Wang, Mihailo R. Jovanovic:
Provably Efficient Generalized Lagrangian Policy Optimization for Safe Multi-Agent Reinforcement Learning. CoRR abs/2306.00212 (2023) - [i124]Nuoya Xiong, Zhaoran Wang, Zhuoran Yang:
A General Framework for Sequential Decision-Making under Adaptivity Constraints. CoRR abs/2306.14468 (2023) - [i123]Pangpang Liu, Zhuoran Yang, Zhaoran Wang, Will Wei Sun:
Contextual Dynamic Pricing with Strategic Buyers. CoRR abs/2307.04055 (2023) - [i122]Zhihan Liu, Hao Hu, Shenao Zhang, Hongyi Guo, Shuqi Ke, Boyi Liu, Zhaoran Wang:
Reason for Future, Act for Now: A Principled Framework for Autonomous LLM Agents with Provable Sample Efficiency. CoRR abs/2309.17382 (2023) - [i121]Nuoya Xiong, Zhihan Liu, Zhaoran Wang, Zhuoran Yang:
Sample-Efficient Multi-Agent RL: An Optimization Perspective. CoRR abs/2310.06243 (2023) - [i120]Chau Pham, Boyi Liu, Yingxiang Yang, Zhengyu Chen, Tianyi Liu, Jianbo Yuan, Bryan A. Plummer, Zhaoran Wang, Hongxia Yang:
Let Models Speak Ciphers: Multiagent Debate through Embeddings. CoRR abs/2310.06272 (2023) - [i119]Fengzhuo Zhang, Vincent Y. F. Tan, Zhaoran Wang, Zhuoran Yang:
Learning Regularized Monotone Graphon Mean-Field Games. CoRR abs/2310.08089 (2023) - [i118]Fengzhuo Zhang, Vincent Y. F. Tan, Zhaoran Wang, Zhuoran Yang:
Learning Regularized Graphon Mean-Field Games with Unknown Graphons. CoRR abs/2310.17531 (2023) - [i117]Shuang Qiu, Ziyu Dai, Han Zhong, Zhaoran Wang, Zhuoran Yang, Tong Zhang:
Posterior Sampling for Competitive RL: Function Approximation and Partial Observation. CoRR abs/2310.19861 (2023) - [i116]Shenao Zhang, Boyi Liu, Zhaoran Wang, Tuo Zhao:
Model-Based Reparameterization Policy Gradient Methods: Theory and Practical Algorithms. CoRR abs/2310.19927 (2023) - [i115]Saizhuo Wang, Zhihan Liu, Zhaoran Wang, Jian Guo:
A Principled Framework for Knowledge-enhanced Large Language Model. CoRR abs/2311.11135 (2023) - [i114]Jianqing Fan, Zhaoran Wang, Zhuoran Yang, Chenlu Ye:
Provably Efficient High-Dimensional Bandit Learning with Batched Feedbacks. CoRR abs/2311.13180 (2023) - [i113]Yixuan Wang, Ruochen Jiao, Chengtian Lang, Simon Sinong Zhan, Chao Huang, Zhaoran Wang, Zhuoran Yang, Qi Zhu:
Empowering Autonomous Driving with Large Language Models: A Safety Perspective. CoRR abs/2312.00812 (2023) - [i112]Quanquan Gu, Zhaoran Wang, Han Liu:
Sparse PCA with Oracle Property. CoRR abs/2312.16793 (2023) - 2022
- [c106]Zehao Dou, Zhuoran Yang, Zhaoran Wang, Simon S. Du:
Gap-Dependent Bounds for Two-Player Markov Games. AISTATS 2022: 432-455 - [c105]Yixuan Wang, Chao Huang, Zhaoran Wang, Zhilu Wang, Qi Zhu:
Design-while-verify: correct-by-construction control learning with verification in the loop. DAC 2022: 925-930 - [c104]Chenjia Bai, Lingxiao Wang, Zhuoran Yang, Zhi-Hong Deng, Animesh Garg, Peng Liu, Zhaoran Wang:
Pessimistic Bootstrapping for Uncertainty-Driven Offline Reinforcement Learning. ICLR 2022 - [c103]Baihe Huang, Jason D. Lee, Zhaoran Wang, Zhuoran Yang:
Towards General Function Approximation in Zero-Sum Markov Games. ICLR 2022 - [c102]Qi Cai, Zhuoran Yang, Zhaoran Wang:
Reinforcement Learning from Partial Observation: Linear Function Approximation with Provable Sample Efficiency. ICML 2022: 2485-2522 - [c101]Siyu Chen, Donglin Yang, Jiayang Li, Senmiao Wang, Zhuoran Yang, Zhaoran Wang:
Adaptive Model Design for Markov Decision Process. ICML 2022: 3679-3700 - [c100]Xiaoyu Chen, Han Zhong, Zhuoran Yang, Zhaoran Wang, Liwei Wang:
Human-in-the-loop: Provably Efficient Preference-based Reinforcement Learning with General Function Approximation. ICML 2022: 3773-3793 - [c99]Hongyi Guo, Qi Cai, Yufeng Zhang, Zhuoran Yang, Zhaoran Wang:
Provably Efficient Offline Reinforcement Learning for Partially Observable Markov Decision Processes. ICML 2022: 8016-8038 - [c98]Zhihan Liu, Miao Lu, Zhaoran Wang, Michael I. Jordan, Zhuoran Yang:
Welfare Maximization in Competitive Equilibrium: Reinforcement Learning for Markov Exchange Economy. ICML 2022: 13870-13911 - [c97]Zhihan Liu, Yufeng Zhang, Zuyue Fu, Zhuoran Yang, Zhaoran Wang:
Learning from Demonstration: Provably Efficient Adversarial Policy Imitation with Linear Function Approximation. ICML 2022: 14094-14138 - [c96]Boxiang Lyu, Zhaoran Wang, Mladen Kolar, Zhuoran Yang:
Pessimism meets VCG: Learning Dynamic Mechanism Design via Offline Reinforcement Learning. ICML 2022: 14601-14638 - [c95]Shuang Qiu, Lingxiao Wang, Chenjia Bai, Zhuoran Yang, Zhaoran Wang:
Contrastive UCB: Provably Efficient Contrastive Self-Supervised Learning in Online Reinforcement Learning. ICML 2022: 18168-18210 - [c94]Han Zhong, Wei Xiong, Jiyuan Tan, Liwei Wang, Tong Zhang, Zhaoran Wang, Zhuoran Yang:
Pessimistic Minimax Value Iteration: Provably Efficient Equilibrium Learning from Offline Datasets. ICML 2022: 27117-27142 - [c93]Gene Li, Junbo Li, Anmol Kabra, Nati Srebro, Zhaoran Wang, Zhuoran Yang:
Exponential Family Model-Based Reinforcement Learning via Score Matching. NeurIPS 2022 - [c92]Boyi Liu, Jiayang Li, Zhuoran Yang, Hoi-To Wai, Mingyi Hong, Yu Nie, Zhaoran Wang:
Inducing Equilibria via Incentives: Simultaneous Design-and-Play Ensures Global Convergence. NeurIPS 2022 - [c91]Xiao-Yang Liu, Ziyi Xia, Jingyang Rui, Jiechao Gao, Hongyang Yang, Ming Zhu, Christina Dan Wang, Zhaoran Wang, Jian Guo:
FinRL-Meta: Market Environments and Benchmarks for Data-Driven Financial Reinforcement Learning. NeurIPS 2022 - [c90]Yifei Min, Tianhao Wang, Ruitu Xu, Zhaoran Wang, Michael I. Jordan, Zhuoran Yang:
Learn to Match with No Regret: Reinforcement Learning in Markov Matching Markets. NeurIPS 2022 - [c89]Tengyu Xu, Zhuoran Yang, Zhaoran Wang, Yingbin Liang:
A Unifying Framework of Off-Policy General Value Function Evaluation. NeurIPS 2022 - [c88]Rui Yang, Chenjia Bai, Xiaoteng Ma, Zhaoran Wang, Chongjie Zhang, Lei Han:
RORL: Robust Offline Reinforcement Learning via Conservative Smoothing. NeurIPS 2022 - [c87]Fengzhuo Zhang, Boyi Liu, Kaixin Wang, Vincent Y. F. Tan, Zhuoran Yang, Zhaoran Wang:
Relational Reasoning via Set Transformers: Provable Efficiency and Applications to MARL. NeurIPS 2022 - [c86]Shichao Xu, Yangyang Fu, Yixuan Wang, Zhuoran Yang, Zheng O'Neill, Zhaoran Wang, Qi Zhu:
Accelerate online reinforcement learning for building HVAC control with heterogeneous expert guidances. BuildSys@SenSys 2022: 89-98 - [c85]Jibang Wu, Zixuan Zhang, Zhe Feng, Zhaoran Wang, Zhuoran Yang, Michael I. Jordan, Haifeng Xu:
Sequential Information Design: Markov Persuasion Process and Its Efficient Reinforcement Learning. EC 2022: 471-472 - [i111]Yixuan Wang, Chao Huang, Zhaoran Wang, Zhuoran Yang, Qi Zhu:
Joint Differentiable Optimization and Verification for Certified Reinforcement Learning. CoRR abs/2201.12243 (2022) - [i110]Han Zhong, Wei Xiong, Jiyuan Tan, Liwei Wang, Tong Zhang, Zhaoran Wang, Zhuoran Yang:
Pessimistic Minimax Value Iteration: Provably Efficient Equilibrium Learning from Offline Datasets. CoRR abs/2202.07511 (2022) - [i109]Jibang Wu, Zixuan Zhang, Zhe Feng, Zhaoran Wang, Zhuoran Yang, Michael I. Jordan, Haifeng Xu:
Sequential Information Design: Markov Persuasion Process and Its Efficient Reinforcement Learning. CoRR abs/2202.10678 (2022) - [i108]Chenjia Bai, Lingxiao Wang, Zhuoran Yang, Zhihong Deng, Animesh Garg, Peng Liu, Zhaoran Wang:
Pessimistic Bootstrapping for Uncertainty-Driven Offline Reinforcement Learning. CoRR abs/2202.11566 (2022) - [i107]Boxiang Lyu, Qinglin Meng, Shuang Qiu, Zhaoran Wang, Zhuoran Yang, Michael I. Jordan:
Learning Dynamic Mechanisms in Unknown Environments: A Reinforcement Learning Approach. CoRR abs/2202.12797 (2022) - [i106]Yifei Min, Tianhao Wang, Ruitu Xu, Zhaoran Wang, Michael I. Jordan, Zhuoran Yang:
Learn to Match with No Regret: Reinforcement Learning in Markov Matching Markets. CoRR abs/2203.03684 (2022) - [i105]Qi Cai, Zhuoran Yang, Zhaoran Wang:
Sample-Efficient Reinforcement Learning for POMDPs with Linear Function Approximations. CoRR abs/2204.09787 (2022) - [i104]Boxiang Lyu, Zhaoran Wang, Mladen Kolar, Zhuoran Yang:
Pessimism meets VCG: Learning Dynamic Mechanism Design via Offline Reinforcement Learning. CoRR abs/2205.02450 (2022) - [i103]Xiaoyu Chen, Han Zhong, Zhuoran Yang, Zhaoran Wang, Liwei Wang:
Human-in-the-loop: Provably Efficient Preference-based Reinforcement Learning with General Function Approximation. CoRR abs/2205.11140 (2022) - [i102]Lingxiao Wang, Qi Cai, Zhuoran Yang, Zhaoran Wang:
Embed to Control Partially Observed Systems: Representation Learning with Provable Sample Efficiency. CoRR abs/2205.13476 (2022) - [i101]Miao Lu, Yifei Min, Zhaoran Wang, Zhuoran Yang:
Pessimism in the Face of Confounders: Provably Efficient Offline Reinforcement Learning in Partially Observable Markov Decision Processes. CoRR abs/2205.13589 (2022) - [i100]Rui Yang, Chenjia Bai, Xiaoteng Ma, Zhaoran Wang, Chongjie Zhang, Lei Han:
RORL: Robust Offline Reinforcement Learning via Conservative Smoothing. CoRR abs/2206.02829 (2022) - [i99]Doudou Zhou, Yufeng Zhang, Aaron Sonabend W., Zhaoran Wang, Junwei Lu, Tianxi Cai:
Federated Offline Reinforcement Learning. CoRR abs/2206.05581 (2022) - [i98]Shuang Qiu, Xiaohan Wei, Jieping Ye, Zhaoran Wang, Zhuoran Yang:
Provably Efficient Fictitious Play Policy Optimization for Zero-Sum Markov Games with Structured Transitions. CoRR abs/2207.12463 (2022) - [i97]Shuang Qiu, Lingxiao Wang, Chenjia Bai, Zhuoran Yang, Zhaoran Wang:
Contrastive UCB: Provably Efficient Contrastive Self-Supervised Learning in Online Reinforcement Learning. CoRR abs/2207.14800 (2022) - [i96]Jiayang Li, Jing Yu, Qianni Wang, Boyi Liu, Zhaoran Wang, Yu Marco Nie:
Differentiable Bilevel Programming for Stackelberg Congestion Games. CoRR abs/2209.07618 (2022) - [i95]Zuyue Fu, Zhengling Qi, Zhaoran Wang, Zhuoran Yang, Yanxun Xu, Michael R. Kosorok:
Offline Reinforcement Learning with Instrumental Variables in Confounded Markov Decision Processes. CoRR abs/2209.08666 (2022) - [i94]Fengzhuo Zhang, Boyi Liu, Kaixin Wang, Vincent Y. F. Tan, Zhuoran Yang, Zhaoran Wang:
Relational Reasoning via Set Transformers: Provable Efficiency and Applications to MARL. CoRR abs/2209.09845 (2022) - [i93]Yixuan Wang, Simon Sinong Zhan, Ruochen Jiao, Zhilu Wang, Wanxin Jin, Zhuoran Yang, Zhaoran Wang, Chao Huang, Qi Zhu:
Enforcing Hard Constraints with Soft Barriers: Safe Reinforcement Learning in Unknown Stochastic Environments. CoRR abs/2209.15090 (2022) - [i92]Rui Ai, Boxiang Lyu, Zhaoran Wang, Zhuoran Yang, Michael I. Jordan:
A Reinforcement Learning Approach in Multi-Phase Second-Price Auction Design. CoRR abs/2210.10278 (2022) - [i91]Han Zhong, Wei Xiong, Sirui Zheng, Liwei Wang, Zhaoran Wang, Zhuoran Yang, Tong Zhang:
GEC: A Unified Framework for Interactive Decision Making in MDP, POMDP, and Beyond. CoRR abs/2211.01962 (2022) - [i90]