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ORCIDZhuoran Yang
This is just a disambiguation page, and is not intended to be the bibliography of an actual person. Any publication listed on this page has not been assigned to an actual author yet. If you know the true author of one of the publications listed below, you are welcome to contact us.
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2020 – today
- 2024
[j20]Chenjia Bai
, Lingxiao Wang, Jianye Hao, Zhuoran Yang, Bin Zhao, Zhen Wang, Xuelong Li:
Pessimistic value iteration for multi-task data sharing in Offline Reinforcement Learning. Artif. Intell. 326: 104048 (2024)- [j19]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) - [j18]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) - [c117]Siyu Chen, Heejune Sheen, Tianhao Wang, Zhuoran Yang:
Training Dynamics of Multi-Head Softmax Attention for In-Context Learning: Emergence, Convergence, and Optimality (extended abstract). COLT 2024: 4573 - [c116]Jianliang He, Han Zhong, Zhuoran Yang:
Sample-efficient Learning of Infinite-horizon Average-reward MDPs with General Function Approximation. ICLR 2024 - [c115]Juno Kim, Kakei Yamamoto, Kazusato Oko, Zhuoran Yang, Taiji Suzuki:
Symmetric Mean-field Langevin Dynamics for Distributional Minimax Problems. ICLR 2024 - [c114]Nuoya Xiong, Zhihan Liu, Zhaoran Wang, Zhuoran Yang:
Sample-Efficient Multi-Agent RL: An Optimization Perspective. ICLR 2024 - [c113]Zehao Dou, Minshuo Chen, Mengdi Wang, Zhuoran Yang:
Theory of Consistency Diffusion Models: Distribution Estimation Meets Fast Sampling. ICML 2024 - [c112]Jianliang He, Siyu Chen, Fengzhuo Zhang, Zhuoran Yang:
From Words to Actions: Unveiling the Theoretical Underpinnings of LLM-Driven Autonomous Systems. ICML 2024 - [c111]Han Shen, Zhuoran Yang, Tianyi Chen:
Principled Penalty-based Methods for Bilevel Reinforcement Learning and RLHF. ICML 2024 - [c110]Nuoya Xiong, Zhaoran Wang, Zhuoran Yang:
A General Framework for Sequential Decision-Making under Adaptivity Constraints. ICML 2024 - [c109]Kakei Yamamoto, Kazusato Oko, Zhuoran Yang, Taiji Suzuki:
Mean Field Langevin Actor-Critic: Faster Convergence and Global Optimality beyond Lazy Learning. ICML 2024 - [c108]Sirui Zheng, Chenjia Bai, Zhuoran Yang, Zhaoran Wang:
How Does Goal Relabeling Improve Sample Efficiency? ICML 2024 - [i128]Han Shen, Zhuoran Yang, Tianyi Chen:
Principled Penalty-based Methods for Bilevel Reinforcement Learning and RLHF. CoRR abs/2402.06886 (2024) - [i127]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) - [i126]Siyu Chen, Heejune Sheen, Tianhao Wang, Zhuoran Yang:
Training Dynamics of Multi-Head Softmax Attention for In-Context Learning: Emergence, Convergence, and Optimality. CoRR abs/2402.19442 (2024) - [i125]Awni Altabaa, Zhuoran Yang:
On the Role of Information Structure in Reinforcement Learning for Partially-Observable Sequential Teams and Games. CoRR abs/2403.00993 (2024) - [i124]Hengyu Fu, Zhuoran Yang, Mengdi Wang, Minshuo Chen:
Unveil Conditional Diffusion Models with Classifier-free Guidance: A Sharp Statistical Theory. CoRR abs/2403.11968 (2024) - [i123]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) - [i122]Jianliang He, Han Zhong, Zhuoran Yang:
Sample-efficient Learning of Infinite-horizon Average-reward MDPs with General Function Approximation. CoRR abs/2404.12648 (2024) - [i121]Chenjia Bai, Lingxiao Wang, Jianye Hao, Zhuoran Yang, Bin Zhao, Zhen Wang, Xuelong Li:
Pessimistic Value Iteration for Multi-Task Data Sharing in Offline Reinforcement Learning. CoRR abs/2404.19346 (2024) - [i120]Chuanhao Li, Runhan Yang, Tiankai Li, Milad Bafarassat, Kourosh Sharifi, Dirk Bergemann, Zhuoran Yang:
STRIDE: A Tool-Assisted LLM Agent Framework for Strategic and Interactive Decision-Making. CoRR abs/2405.16376 (2024) - [i119]Jianliang He, Siyu Chen, Fengzhuo Zhang, Zhuoran Yang:
From Words to Actions: Unveiling the Theoretical Underpinnings of LLM-Driven Autonomous Systems. CoRR abs/2405.19883 (2024) - [i118]Zehao Dou, Minshuo Chen, Mengdi Wang, Zhuoran Yang:
Provable Statistical Rates for Consistency Diffusion Models. CoRR abs/2406.16213 (2024) - 2023
- [j17]Zhuoran Yang, Yuan Gao, Jingfang Deng, Lixiang Lv:
Partial Discharge Characteristics and Growth Stage Recognition of Electrical Tree in XLPE Insulation. IEEE Access 11: 145527-145535 (2023) - [j16]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) - [j15]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) - [j14]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) - [j13]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) - [j12]Nikola Banovic, Zhuoran Yang, Aditya Ramesh, Alice Liu:
Being Trustworthy is Not Enough: How Untrustworthy Artificial Intelligence (AI) Can Deceive the End-Users and Gain Their Trust. Proc. ACM Hum. Comput. Interact. 7(CSCW1): 1-17 (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) - [c107]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 - [c106]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 - [c105]Lingxiao Wang, Qi Cai, Zhuoran Yang, Zhaoran Wang:
Represent to Control Partially Observed Systems: Representation Learning with Provable Sample Efficiency. ICLR 2023 - [c104]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 - [c103]Zhuoqing Song, Jason D. Lee, Zhuoran Yang:
Can We Find Nash Equilibria at a Linear Rate in Markov Games? ICLR 2023 - [c102]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 - [c101]Wenhao Zhan, Jason D. Lee, Zhuoran Yang:
Decentralized Optimistic Hyperpolicy Mirror Descent: Provably No-Regret Learning in Markov Games. ICLR 2023 - [c100]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 - [c99]Siyu Chen, Jibang Wu, Yifan Wu, Zhuoran Yang:
Learning to Incentivize Information Acquisition: Proper Scoring Rules Meet Principal-Agent Model. ICML 2023: 5194-5218 - [c98]Jiacheng Guo, Zihao Li, Huazheng Wang, Mengdi Wang, Zhuoran Yang, Xuezhou Zhang:
Provably Efficient Representation Learning with Tractable Planning in Low-Rank POMDP. ICML 2023: 11967-11997 - [c97]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 - [c96]Yulai Zhao, Zhuoran Yang, Zhaoran Wang, Jason D. Lee:
Local Optimization Achieves Global Optimality in Multi-Agent Reinforcement Learning. ICML 2023: 42200-42226 - [c95]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 - [c94]Haoran He, Chenjia Bai, Kang Xu, Zhuoran Yang, Weinan Zhang, Dong Wang, Bin Zhao, Xuelong Li:
Diffusion Model is an Effective Planner and Data Synthesizer for Multi-Task Reinforcement Learning. NeurIPS 2023 - [c93]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 - [c92]Shuang Qiu, Ziyu Dai, Han Zhong, Zhaoran Wang, Zhuoran Yang, Tong Zhang:
Posterior Sampling for Competitive RL: Function Approximation and Partial Observation. NeurIPS 2023 - [c91]Fengzhuo Zhang, Vincent Y. F. Tan, Zhaoran Wang, Zhuoran Yang:
Learning Regularized Monotone Graphon Mean-Field Games. NeurIPS 2023 - [c90]Zihan Zhu, Ethan Fang, Zhuoran Yang:
Online Performative Gradient Descent for Learning Nash Equilibria in Decision-Dependent Games. NeurIPS 2023 - [c89]Banghua Zhu, Stephen Bates, Zhuoran Yang, Yixin Wang, Jiantao Jiao, Michael I. Jordan:
The Sample Complexity of Online Contract Design. EC 2023: 1188 - [i117]Zhuoqing Song, Jason D. Lee, Zhuoran Yang:
Can We Find Nash Equilibria at a Linear Rate in Markov Games? CoRR abs/2303.03095 (2023) - [i116]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) - [i115]Siyu Chen, Jibang Wu, Yifan Wu, Zhuoran Yang:
Learning to Incentivize Information Acquisition: Proper Scoring Rules Meet Principal-Agent Model. CoRR abs/2303.08613 (2023) - [i114]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) - [i113]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) - [i112]Yulai Zhao, Zhuoran Yang, Zhaoran Wang, Jason D. Lee:
Local Optimization Achieves Global Optimality in Multi-Agent Reinforcement Learning. CoRR abs/2305.04819 (2023) - [i111]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) - [i110]Zihao Li, Zhuoran Yang, Mengdi Wang:
Reinforcement Learning with Human Feedback: Learning Dynamic Choices via Pessimism. CoRR abs/2305.18438 (2023) - [i109]Haoran He, Chenjia Bai, Kang Xu, Zhuoran Yang, Weinan Zhang, Dong Wang, Bin Zhao, Xuelong Li:
Diffusion Model is an Effective Planner and Data Synthesizer for Multi-Task Reinforcement Learning. CoRR abs/2305.18459 (2023) - [i108]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) - [i107]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) - [i106]Jiacheng Guo, Zihao Li, Huazheng Wang, Mengdi Wang, Zhuoran Yang, Xuezhou Zhang:
Provably Efficient Representation Learning with Tractable Planning in Low-Rank POMDP. CoRR abs/2306.12356 (2023) - [i105]Nuoya Xiong, Zhaoran Wang, Zhuoran Yang:
A General Framework for Sequential Decision-Making under Adaptivity Constraints. CoRR abs/2306.14468 (2023) - [i104]Pangpang Liu, Zhuoran Yang, Zhaoran Wang, Will Wei Sun:
Contextual Dynamic Pricing with Strategic Buyers. CoRR abs/2307.04055 (2023) - [i103]Siyu Chen, Mengdi Wang, Zhuoran Yang:
Actions Speak What You Want: Provably Sample-Efficient Reinforcement Learning of the Quantal Stackelberg Equilibrium from Strategic Feedbacks. CoRR abs/2307.14085 (2023) - [i102]Nuoya Xiong, Zhihan Liu, Zhaoran Wang, Zhuoran Yang:
Sample-Efficient Multi-Agent RL: An Optimization Perspective. CoRR abs/2310.06243 (2023) - [i101]Fengzhuo Zhang, Vincent Y. F. Tan, Zhaoran Wang, Zhuoran Yang:
Learning Regularized Monotone Graphon Mean-Field Games. CoRR abs/2310.08089 (2023) - [i100]Fengzhuo Zhang, Vincent Y. F. Tan, Zhaoran Wang, Zhuoran Yang:
Learning Regularized Graphon Mean-Field Games with Unknown Graphons. CoRR abs/2310.17531 (2023) - [i99]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) - [i98]Jianqing Fan, Zhaoran Wang, Zhuoran Yang, Chenlu Ye:
Provably Efficient High-Dimensional Bandit Learning with Batched Feedbacks. CoRR abs/2311.13180 (2023) - [i97]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) - 2022
- [c88]Zehao Dou, Zhuoran Yang, Zhaoran Wang, Simon S. Du:
Gap-Dependent Bounds for Two-Player Markov Games. AISTATS 2022: 432-455 - [c87]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 - [c86]Baihe Huang, Jason D. Lee, Zhaoran Wang, Zhuoran Yang:
Towards General Function Approximation in Zero-Sum Markov Games. ICLR 2022 - [c85]Zhi Zhang, Zhuoran Yang, Han Liu, Pratap Tokekar, Furong Huang:
Reinforcement Learning under a Multi-agent Predictive State Representation Model: Method and Theory. ICLR 2022 - [c84]Qi Cai, Zhuoran Yang, Zhaoran Wang:
Reinforcement Learning from Partial Observation: Linear Function Approximation with Provable Sample Efficiency. ICML 2022: 2485-2522 - [c83]Siyu Chen, Donglin Yang, Jiayang Li, Senmiao Wang, Zhuoran Yang, Zhaoran Wang:
Adaptive Model Design for Markov Decision Process. ICML 2022: 3679-3700 - [c82]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 - [c81]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 - [c80]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 - [c79]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 - [c78]Boxiang Lyu, Zhaoran Wang, Mladen Kolar, Zhuoran Yang:
Pessimism meets VCG: Learning Dynamic Mechanism Design via Offline Reinforcement Learning. ICML 2022: 14601-14638 - [c77]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 - [c76]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 - [c75]Gene Li, Junbo Li, Anmol Kabra, Nati Srebro, Zhaoran Wang, Zhuoran Yang:
Exponential Family Model-Based Reinforcement Learning via Score Matching. NeurIPS 2022 - [c74]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 - [c73]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 - [c72]Grigoris Velegkas, Zhuoran Yang, Amin Karbasi:
Reinforcement Learning with Logarithmic Regret and Policy Switches. NeurIPS 2022 - [c71]Tengyu Xu, Zhuoran Yang, Zhaoran Wang, Yingbin Liang:
A Unifying Framework of Off-Policy General Value Function Evaluation. NeurIPS 2022 - [c70]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 - [c69]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 - [c68]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 - [i96]Yixuan Wang, Chao Huang, Zhaoran Wang, Zhuoran Yang, Qi Zhu:
Joint Differentiable Optimization and Verification for Certified Reinforcement Learning. CoRR abs/2201.12243 (2022) - [i95]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) - [i94]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) - [i93]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) - [i92]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) - [i91]Grigoris Velegkas, Zhuoran Yang, Amin Karbasi:
The Best of Both Worlds: Reinforcement Learning with Logarithmic Regret and Policy Switches. CoRR abs/2203.01491 (2022) - [i90]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) - [i89]Qi Cai, Zhuoran Yang, Zhaoran Wang:
Sample-Efficient Reinforcement Learning for POMDPs with Linear Function Approximations. CoRR abs/2204.09787 (2022) - [i88]Boxiang Lyu, Zhaoran Wang, Mladen Kolar, Zhuoran Yang:
Pessimism meets VCG: Learning Dynamic Mechanism Design via Offline Reinforcement Learning. CoRR abs/2205.02450 (2022) - [i87]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) - [i86]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) - [i85]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) - [i84]Wenhao Zhan, Jason D. Lee, Zhuoran Yang:
Decentralized Optimistic Hyperpolicy Mirror Descent: Provably No-Regret Learning in Markov Games. CoRR abs/2206.01588 (2022) - [i83]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) - [i82]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) - [i81]Mengxin Yu, Zhuoran Yang, Jianqing Fan:
Strategic Decision-Making in the Presence of Information Asymmetry: Provably Efficient RL with Algorithmic Instruments. CoRR abs/2208.11040 (2022) - [i80]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) - [i79]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) - [i78]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) - [i77]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) - [i76]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) - [i75]