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2020 – today
- 2022
[c81]Zehao Dou, Zhuoran Yang, Zhaoran Wang, Simon S. Du:
Gap-Dependent Bounds for Two-Player Markov Games. AISTATS 2022: 432-455- [c80]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 - [c79]Baihe Huang, Jason D. Lee, Zhaoran Wang, Zhuoran Yang:
Towards General Function Approximation in Zero-Sum Markov Games. ICLR 2022 - [c78]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 - [c77]Qi Cai, Zhuoran Yang, Zhaoran Wang:
Reinforcement Learning from Partial Observation: Linear Function Approximation with Provable Sample Efficiency. ICML 2022: 2485-2522 - [c76]Siyu Chen, Donglin Yang, Jiayang Li, Senmiao Wang, Zhuoran Yang, Zhaoran Wang:
Adaptive Model Design for Markov Decision Process. ICML 2022: 3679-3700 - [c75]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 - [c74]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 - [c73]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 - [c72]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 - [c71]Boxiang Lyu, Zhaoran Wang, Mladen Kolar, Zhuoran Yang:
Pessimism meets VCG: Learning Dynamic Mechanism Design via Offline Reinforcement Learning. ICML 2022: 14601-14638 - [c70]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 - [c69]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 - [c68]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 - [c67]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]Banghua Zhu, Stephen Bates, Zhuoran Yang, Yixin Wang, Jiantao Jiao, Michael I. Jordan:
The Sample Complexity of Online Contract Design. CoRR abs/2211.05732 (2022) - [i74]Ying Jin, Zhimei Ren, Zhuoran Yang, Zhaoran Wang:
Policy learning "without" overlap: Pessimism and generalized empirical Bernstein's inequality. CoRR abs/2212.09900 (2022) - [i73]Zuyue Fu, Zhengling Qi, Zhuoran Yang, Zhaoran Wang, Lan Wang:
Offline Reinforcement Learning for Human-Guided Human-Machine Interaction with Private Information. CoRR abs/2212.12167 (2022) - [i72]Riashat Islam, Samarth Sinha, Homanga Bharadhwaj, Samin Yeasar Arnob, Zhuoran Yang, Animesh Garg, Zhaoran Wang, Lihong Li, Doina Precup:
Offline Policy Optimization in RL with Variance Regularizaton. CoRR abs/2212.14405 (2022) - 2021
- [j10]Liya Fu, Zhuoran Yang, Jun Zhang, Anle Long, Yan Zhou:
Generalized estimating equations for analyzing multivariate survival data. Commun. Stat. Simul. Comput. 50(10): 3060-3068 (2021) - [j9]Liya Fu, Zhuoran Yang, Fengjing Cai, You-Gan Wang
:
Efficient and doubly-robust methods for variable selection and parameter estimation in longitudinal data analysis. Comput. Stat. 36(2): 781-804 (2021) - [j8]Shuang Qiu, Zhuoran Yang, Jieping Ye, Zhaoran Wang:
On Finite-Time Convergence of Actor-Critic Algorithm. IEEE J. Sel. Areas Inf. Theory 2(2): 652-664 (2021) - [j7]Kaiqing Zhang, Zhuoran Yang, Tamer Basar:
Decentralized multi-agent reinforcement learning with networked agents: recent advances. Frontiers Inf. Technol. Electron. Eng. 22(6): 802-814 (2021) - [j6]Kaiqing Zhang, Zhuoran Yang, Han Liu, Tong Zhang, Tamer Basar:
Finite-Sample Analysis for Decentralized Batch Multiagent Reinforcement Learning With Networked Agents. IEEE Trans. Autom. Control. 66(12): 5925-5940 (2021) - [c66]Jiaheng Wei, Zuyue Fu, Yang Liu, Xingyu Li, Zhuoran Yang, Zhaoran Wang:
Sample Elicitation. AISTATS 2021: 2692-2700 - [c65]Yufeng Zhang, Zhuoran Yang, Zhaoran Wang:
Provably Efficient Actor-Critic for Risk-Sensitive and Robust Adversarial RL: A Linear-Quadratic Case. AISTATS 2021: 2764-2772 - [c64]Dongsheng Ding, Xiaohan Wei, Zhuoran Yang, Zhaoran Wang, Mihailo R. Jovanovic:
Provably Efficient Safe Exploration via Primal-Dual Policy Optimization. AISTATS 2021: 3304-3312 - [c63]Zuyue Fu, Zhuoran Yang, Zhaoran Wang:
Single-Timescale Actor-Critic Provably Finds Globally Optimal Policy. ICLR 2021 - [c62]Yingjie Fei, Zhuoran Yang, Zhaoran Wang:
Risk-Sensitive Reinforcement Learning with Function Approximation: A Debiasing Approach. ICML 2021: 3198-3207 - [c61]Hongyi Guo, Zuyue Fu, Zhuoran Yang, Zhaoran Wang:
Decentralized Single-Timescale Actor-Critic on Zero-Sum Two-Player Stochastic Games. ICML 2021: 3899-3909 - [c60]Haque Ishfaq, Qiwen Cui, Viet Nguyen, Alex Ayoub, Zhuoran Yang, Zhaoran Wang, Doina Precup, Lin Yang:
Randomized Exploration in Reinforcement Learning with General Value Function Approximation. ICML 2021: 4607-4616 - [c59]Ying Jin, Zhuoran Yang, Zhaoran Wang:
Is Pessimism Provably Efficient for Offline RL? ICML 2021: 5084-5096 - [c58]Lewis Liu, Yufeng Zhang, Zhuoran Yang, Reza Babanezhad, Zhaoran Wang:
Infinite-Dimensional Optimization for Zero-Sum Games via Variational Transport. ICML 2021: 7033-7044 - [c57]Shuang Qiu, Xiaohan Wei, Jieping Ye, Zhaoran Wang, Zhuoran Yang:
Provably Efficient Fictitious Play Policy Optimization for Zero-Sum Markov Games with Structured Transitions. ICML 2021: 8715-8725 - [c56]Shuang Qiu, Jieping Ye, Zhaoran Wang, Zhuoran Yang:
On Reward-Free RL with Kernel and Neural Function Approximations: Single-Agent MDP and Markov Game. ICML 2021: 8737-8747 - [c55]Wesley Suttle, Kaiqing Zhang, Zhuoran Yang, Ji Liu, David Kraemer:
Reinforcement Learning for Cost-Aware Markov Decision Processes. ICML 2021: 9989-9999 - [c54]Weichen Wang, Jiequn Han, Zhuoran Yang, Zhaoran Wang:
Global Convergence of Policy Gradient for Linear-Quadratic Mean-Field Control/Game in Continuous Time. ICML 2021: 10772-10782 - [c53]Qiaomin Xie, Zhuoran Yang, Zhaoran Wang, Andreea Minca:
Learning While Playing in Mean-Field Games: Convergence and Optimality. ICML 2021: 11436-11447 - [c52]Tengyu Xu, Zhuoran Yang, Zhaoran Wang, Yingbin Liang:
Doubly Robust Off-Policy Actor-Critic: Convergence and Optimality. ICML 2021: 11581-11591 - [c51]Jingwei Zhang, Zhuoran Yang, Zhengyuan Zhou, Zhaoran Wang:
Provably Sample Efficient Reinforcement Learning in Competitive Linear Quadratic Systems. L4DC 2021: 597-598 - [c50]Boyi Liu, Qi Cai, Zhuoran Yang, Zhaoran Wang:
BooVI: Provably Efficient Bootstrapped Value Iteration. NeurIPS 2021: 7041-7053 - [c49]Yufeng Zhang, Siyu Chen, Zhuoran Yang, Michael I. Jordan, Zhaoran Wang:
Wasserstein Flow Meets Replicator Dynamics: A Mean-Field Analysis of Representation Learning in Actor-Critic. NeurIPS 2021: 15993-16006 - [c48]Minshuo Chen, Yan Li, Ethan Wang, Zhuoran Yang, Zhaoran Wang, Tuo Zhao:
Pessimism Meets Invariance: Provably Efficient Offline Mean-Field Multi-Agent RL. NeurIPS 2021: 17913-17926 - [c47]Yingjie Fei, Zhuoran Yang, Yudong Chen, Zhaoran Wang:
Exponential Bellman Equation and Improved Regret Bounds for Risk-Sensitive Reinforcement Learning. NeurIPS 2021: 20436-20446 - [c46]Lingxiao Wang, Zhuoran Yang, Zhaoran Wang:
Provably Efficient Causal Reinforcement Learning with Confounded Observational Data. NeurIPS 2021: 21164-21175 - [c45]Runzhe Wu, Yufeng Zhang, Zhuoran Yang, Zhaoran Wang:
Offline Constrained Multi-Objective Reinforcement Learning via Pessimistic Dual Value Iteration. NeurIPS 2021: 25439-25451 - [c44]Prashant Khanduri, Siliang Zeng, Mingyi Hong, Hoi-To Wai, Zhaoran Wang, Zhuoran Yang:
A Near-Optimal Algorithm for Stochastic Bilevel Optimization via Double-Momentum. NeurIPS 2021: 30271-30283 - [i71]Prashant Khanduri, Siliang Zeng, Mingyi Hong, Hoi-To Wai, Zhaoran Wang, Zhuoran Yang:
A Momentum-Assisted Single-Timescale Stochastic Approximation Algorithm for Bilevel Optimization. CoRR abs/2102.07367 (2021) - [i70]Luofeng Liao, Zuyue Fu, Zhuoran Yang, Mladen Kolar, Zhaoran Wang:
Instrumental Variable Value Iteration for Causal Offline Reinforcement Learning. CoRR abs/2102.09907 (2021) - [i69]Tengyu Xu, Zhuoran Yang, Zhaoran Wang, Yingbin Liang:
Doubly Robust Off-Policy Actor-Critic: Convergence and Optimality. CoRR abs/2102.11866 (2021) - [i68]Haque Ishfaq, Qiwen Cui, Viet Nguyen, Alex Ayoub, Zhuoran Yang, Zhaoran Wang, Doina Precup, Lin F. Yang:
Randomized Exploration for Reinforcement Learning with General Value Function Approximation. CoRR abs/2106.07841 (2021) - [i67]Zehao Dou, Zhuoran Yang, Zhaoran Wang, Simon S. Du:
Gap-Dependent Bounds for Two-Player Markov Games. CoRR abs/2107.00685 (2021) - [i66]Tengyu Xu, Zhuoran Yang, Zhaoran Wang, Yingbin Liang:
A Unified Off-Policy Evaluation Approach for General Value Function. CoRR abs/2107.02711 (2021) - [i65]Baihe Huang, Jason D. Lee, Zhaoran Wang, Zhuoran Yang:
Towards General Function Approximation in Zero-Sum Markov Games. CoRR abs/2107.14702 (2021) - [i64]Pratik Ramprasad, Yuantong Li, Zhuoran Yang, Zhaoran Wang, Will Wei Sun, Guang Cheng:
Online Bootstrap Inference For Policy Evaluation in Reinforcement Learning. CoRR abs/2108.03706 (2021) - [i63]Zhihan Liu, Yufeng Zhang, Zuyue Fu, Zhuoran Yang, Zhaoran Wang:
Provably Efficient Generative Adversarial Imitation Learning for Online and Offline Setting with Linear Function Approximation. CoRR abs/2108.08765 (2021) - [i62]Boyi Liu, Jiayang Li, Zhuoran Yang, Hoi-To Wai, Mingyi Hong, Yu Marco Nie, Zhaoran Wang:
Inducing Equilibria via Incentives: Simultaneous Design-and-Play Finds Global Optima. CoRR abs/2110.01212 (2021) - [i61]Han Zhong, Zhuoran Yang, Zhaoran Wang, Csaba Szepesvári:
Optimistic Policy Optimization is Provably Efficient in Non-stationary MDPs. CoRR abs/2110.08984 (2021) - [i60]Shuang Qiu, Jieping Ye, Zhaoran Wang, Zhuoran Yang:
On Reward-Free RL with Kernel and Neural Function Approximations: Single-Agent MDP and Markov Game. CoRR abs/2110.09771 (2021) - [i59]Zhihong Deng, Zuyue Fu, Lingxiao Wang, Zhuoran Yang, Chenjia Bai, Zhaoran Wang, Jing Jiang:
SCORE: Spurious COrrelation REduction for Offline Reinforcement Learning. CoRR abs/2110.12468 (2021) - [i58]Yingjie Fei, Zhuoran Yang, Yudong Chen, Zhaoran Wang:
Exponential Bellman Equation and Improved Regret Bounds for Risk-Sensitive Reinforcement Learning. CoRR abs/2111.03947 (2021) - [i57]Xiao-Yang Liu, Zechu Li, Zhuoran Yang, Jiahao Zheng, Zhaoran Wang, Anwar Walid, Jian Guo, Michael I. Jordan:
ElegantRL-Podracer: Scalable and Elastic Library for Cloud-Native Deep Reinforcement Learning. CoRR abs/2112.05923 (2021) - [i56]Han Zhong, Zhuoran Yang, Zhaoran Wang, Michael I. Jordan:
Can Reinforcement Learning Find Stackelberg-Nash Equilibria in General-Sum Markov Games with Myopic Followers? CoRR abs/2112.13521 (2021) - [i55]Yufeng Zhang, Siyu Chen, Zhuoran Yang, Michael I. Jordan, Zhaoran Wang:
Wasserstein Flow Meets Replicator Dynamics: A Mean-Field Analysis of Representation Learning in Actor-Critic. CoRR abs/2112.13530 (2021) - [i54]Gene Li, Junbo Li, Nathan Srebro, Zhaoran Wang, Zhuoran Yang:
Exponential Family Model-Based Reinforcement Learning via Score Matching. CoRR abs/2112.14195 (2021) - 2020
- [j5]Yubo Zhang, Zhuoran Yang, Jiuchun Yang, Yuanyuan Yang, Dongyan Wang, Yucong Zhang, Fengqin Yan, Lingxue Yu, Liping Chang, Shuwen Zhang:
A Novel Model Integrating Deep Learning for Land Use/Cover Change Reconstruction: A Case Study of Zhenlai County, Northeast China. Remote. Sens. 12(20): 3314 (2020) - [c43]Chi Jin, Zhuoran Yang, Zhaoran Wang, Michael I. Jordan:
Provably efficient reinforcement learning with linear function approximation. COLT 2020: 2137-2143 - [c42]Qiaomin Xie, Yudong Chen, Zhaoran Wang, Zhuoran Yang:
Learning Zero-Sum Simultaneous-Move Markov Games Using Function Approximation and Correlated Equilibrium. COLT 2020: 3674-3682 - [c41]Minshuo Chen, Yizhou Wang, Tianyi Liu, Zhuoran Yang, Xingguo Li, Zhaoran Wang, Tuo Zhao:
On Computation and Generalization of Generative Adversarial Imitation Learning. ICLR 2020 - [c40]Zuyue Fu, Zhuoran Yang, Yongxin Chen, Zhaoran Wang:
Actor-Critic Provably Finds Nash Equilibria of Linear-Quadratic Mean-Field Games. ICLR 2020 - [c39]Lingxiao Wang, Qi Cai, Zhuoran Yang, Zhaoran Wang:
Neural Policy Gradient Methods: Global Optimality and Rates of Convergence. ICLR 2020 - [c38]Qi Cai, Zhuoran Yang, Chi Jin, Zhaoran Wang:
Provably Efficient Exploration in Policy Optimization. ICML 2020: 1283-1294 - [c37]Sen Na, Yuwei Luo, Zhuoran Yang, Zhaoran Wang, Mladen Kolar:
Semiparametric Nonlinear Bipartite Graph Representation Learning with Provable Guarantees. ICML 2020: 7141-7152 - [c36]Shuang Qiu, Xiaohan Wei, Zhuoran Yang:
Robust One-Bit Recovery via ReLU Generative Networks: Near-Optimal Statistical Rate and Global Landscape Analysis. ICML 2020: 7857-7866 - [c35]Lingxiao Wang, Qi Cai, Zhuoran Yang, Zhaoran Wang:
On the Global Optimality of Model-Agnostic Meta-Learning. ICML 2020: 9837-9846 - [c34]Lingxiao Wang, Zhuoran Yang, Zhaoran Wang:
Breaking the Curse of Many Agents: Provable Mean Embedding Q-Iteration for Mean-Field Reinforcement Learning. ICML 2020: 10092-10103 - [c33]Yufeng Zhang, Qi Cai, Zhuoran Yang, Zhaoran Wang:
Generative Adversarial Imitation Learning with Neural Network Parameterization: Global Optimality and Convergence Rate. ICML 2020: 11044-11054 - [c32]Jianqing Fan, Zhaoran Wang, Yuchen Xie, Zhuoran Yang:
A Theoretical Analysis of Deep Q-Learning. L4DC 2020: 486-489 - [c31]Yingjie Fei, Zhuoran Yang, Yudong Chen, Zhaoran Wang, Qiaomin Xie:
Risk-Sensitive Reinforcement Learning: Near-Optimal Risk-Sample Tradeoff in Regret. NeurIPS 2020 - [c30]Yingjie Fei, Zhuoran Yang, Zhaoran Wang, Qiaomin Xie:
Dynamic Regret of Policy Optimization in Non-Stationary Environments. NeurIPS 2020 - [c29]Wanxin Jin, Zhaoran Wang, Zhuoran Yang, Shaoshuai Mou:
Pontryagin Differentiable Programming: An End-to-End Learning and Control Framework. NeurIPS 2020 - [c28]Luofeng Liao, You-Lin Chen, Zhuoran Yang, Bo Dai, Mladen Kolar, Zhaoran Wang:
Provably Efficient Neural Estimation of Structural Equation Models: An Adversarial Approach. NeurIPS 2020 - [c27]Shuang Qiu, Xiaohan Wei, Zhuoran Yang, Jieping Ye, Zhaoran Wang:
Upper Confidence Primal-Dual Reinforcement Learning for CMDP with Adversarial Loss. NeurIPS 2020 - [c26]Hoi-To Wai, Zhuoran Yang, Zhaoran Wang, Mingyi Hong:
Provably Efficient Neural GTD for Off-Policy Learning. NeurIPS 2020 - [c25]Zhuoran Yang, Chi Jin, Zhaoran Wang, Mengdi Wang, Michael I. Jordan:
Provably Efficient Reinforcement Learning with Kernel and Neural Function Approximations. NeurIPS 2020 - [c24]Yufeng Zhang, Qi Cai, Zhuoran Yang, Yongxin Chen, Zhaoran Wang:
Can Temporal-Difference and Q-Learning Learn Representation? A Mean-Field Theory. NeurIPS 2020 - [i53]Minshuo Chen, Yizhou Wang, Tianyi Liu, Zhuoran Yang, Xingguo Li, Zhaoran Wang, Tuo Zhao:
On Computation and Generalization of Generative Adversarial Imitation Learning. CoRR abs/2001.02792 (2020) - [i52]Qiaomin Xie, Yudong Chen, Zhaoran Wang, Zhuoran Yang:
Learning Zero-Sum Simultaneous-Move Markov Games Using Function Approximation and Correlated Equilibrium. CoRR abs/2002.07066 (2020) - [i51]Dongsheng Ding, Xiaohan Wei, Zhuoran Yang, Zhaoran Wang, Mihailo R. Jovanovic:
Provably Efficient Safe Exploration via Primal-Dual Policy Optimization. CoRR abs/2003.00534 (2020) - [i50]Shuang Qiu, Xiaohan Wei, Zhuoran Yang, Jieping Ye, Zhaoran Wang:
Upper Confidence Primal-Dual Optimization: Stochastically Constrained Markov Decision Processes with Adversarial Losses and Unknown Transitions. CoRR abs/2003.00660 (2020) - [i49]Sen Na, Yuwei Luo, Zhuoran Yang, Zhaoran Wang, Mladen Kolar:
Semiparametric Nonlinear Bipartite Graph Representation Learning with Provable Guarantees. CoRR abs/2003.01013 (2020) - [i48]Yufeng Zhang, Qi Cai, Zhuoran Yang, Zhaoran Wang:
Generative Adversarial Imitation Learning with Neural Networks: Global Optimality and Convergence Rate. CoRR abs/2003.03709 (2020) - [i47]Yufeng Zhang, Qi Cai, Zhuoran Yang, Yongxin Chen, Zhaoran Wang:
Can Temporal-Difference and Q-Learning Learn Representation? A Mean-Field Theory. CoRR abs/2006.04761 (2020) - [i46]Wanxin Jin, Zhaoran Wang, Zhuoran Yang, Shaoshuai Mou:
Neural Certificates for Safe Control Policies. CoRR abs/2006.08465 (2020) - [i45]Lingxiao Wang, Zhuoran Yang, Zhaoran Wang:
Breaking the Curse of Many Agents: Provable Mean Embedding Q-Iteration for Mean-Field Reinforcement Learning. CoRR abs/2006.11917 (2020) - [i44]Lingxiao Wang, Zhuoran Yang, Zhaoran Wang:
Provably Efficient Causal Reinforcement Learning with Confounded Observational Data. CoRR abs/2006.12311 (2020) - [i43]