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ORCIDZhaoran Wang 0001
Person information
- affiliation: Northwestern University, Evanston, IL, USA
Other persons with the same name
- Zhaoran Wang
- Zhaoran Wang 0002
![[0009-0005-2961-7324]](https://dblp.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
[j20]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)- [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) - [j17]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) - [j16]Jiayang Li, Zhaoran Wang, Yu Marco Nie:
Wardrop Equilibrium Can Be Boundedly Rational: A New Behavioral Theory of Route Choice. Transp. Sci. 58(5): 973-994 (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 - [i150]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) - [i149]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) - [i148]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) - [i147]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) - [i146]Mengying Lin, Yaran Chen, Dongbin Zhao, Zhaoran Wang:
Advancing Object Goal Navigation Through LLM-enhanced Object Affinities Transfer. CoRR abs/2403.09971 (2024) - [i145]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) - [i144]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) - [i143]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) - [i142]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) - [i141]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) - [i140]Ruijie Xu, Zhihan Liu, Yongfei Liu, Shipeng Yan, Zhaoran Wang, Zhi Zhang, Xuming He:
Just say what you want: only-prompting self-rewarding online preference optimization. CoRR abs/2409.17534 (2024) - [i139]Shenao Zhang, Zhihan Liu, Boyi Liu, Yufeng Zhang, Yingxiang Yang, Yongfei Liu, Liyu Chen, Tao Sun, Zhaoran Wang:
Reward-Augmented Data Enhances Direct Preference Alignment of LLMs. CoRR abs/2410.08067 (2024) - [i138]Harsh Mahesheka, Zhixian Xie, Zhaoran Wang, Wanxin Jin:
Language-Model-Assisted Bi-Level Programming for Reward Learning from Internet Videos. CoRR abs/2410.09286 (2024) - [i137]Zhihan Liu, Shenao Zhang, Zhaoran Wang:
DSTC: Direct Preference Learning with Only Self-Generated Tests and Code to Improve Code LMs. CoRR abs/2411.13611 (2024) - [i136]Rui Ai, Boxiang Lyu, Zhaoran Wang, Zhuoran Yang, Haifeng Xu:
An Instrumental Value for Data Production and its Application to Data Pricing. CoRR abs/2412.18140 (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 Marco 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 Marco 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 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]Tongzheng Ren, Chenjun Xiao, Tianjun Zhang, Na Li, Zhaoran Wang, Sujay Sanghavi, Dale Schuurmans, Bo Dai:
Latent Variable Representation for Reinforcement Learning. CoRR abs/2212.08765 (2022) - [i89]Ying Jin, Zhimei Ren, Zhuoran Yang, Zhaoran Wang:
Policy learning "without" overlap: Pessimism and generalized empirical Bernstein's inequality. CoRR abs/2212.09900 (2022) - [i88]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) - [i87]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) - [i86]Yufeng Zhang, Boyi Liu, Qi Cai, Lingxiao Wang, Zhaoran Wang:
An Analysis of Attention via the Lens of Exchangeability and Latent Variable Models. CoRR abs/2212.14852 (2022) - 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]Lewis Liu, Songtao Lu, Tuo Zhao, Zhaoran Wang:
Spectrum Truncation Power Iteration for Agnostic Matrix Phase Retrieval. IEEE Trans. Signal Process. 69: 3991-4006 (2021) - [c84]Jiaheng Wei, Zuyue Fu, Yang Liu, Xingyu Li, Zhuoran Yang, Zhaoran Wang:
Sample Elicitation. AISTATS 2021: 2692-2700 - [c83]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 - [c82]Dongsheng Ding, Xiaohan Wei, Zhuoran Yang, Zhaoran Wang, Mihailo R. Jovanovic:
Provably Efficient Safe Exploration via Primal-Dual Policy Optimization. AISTATS 2021: 3304-3312 - [c81]Yixuan Wang, Chao Huang, Zhilu Wang, Shichao Xu, Zhaoran Wang, Qi Zhu:
Cocktail: Learn a Better Neural Network Controller from Multiple Experts via Adaptive Mixing and Robust Distillation. DAC 2021: 397-402 - [c80]Zechu Li, Xiao-Yang Liu, Jiahao Zheng, Zhaoran Wang, Anwar Walid, Jian Guo:
FinRL-podracer: high performance and scalable deep reinforcement learning for quantitative finance. ICAIF 2021: 48:1-48:9 - [c79]Zuyue Fu, Zhuoran Yang, Zhaoran Wang:
Single-Timescale Actor-Critic Provably Finds Globally Optimal Policy. ICLR 2021 - [c78]Chenjia Bai, Lingxiao Wang, Lei Han, Jianye Hao, Animesh Garg, Peng Liu, Zhaoran Wang:
Principled Exploration via Optimistic Bootstrapping and Backward Induction. ICML 2021: 577-587 - [c77]Yingjie Fei, Zhuoran Yang, Zhaoran Wang:
Risk-Sensitive Reinforcement Learning with Function Approximation: A Debiasing Approach. ICML 2021: 3198-3207 - [c76]Hongyi Guo, Zuyue Fu, Zhuoran Yang, Zhaoran Wang:
Decentralized Single-Timescale Actor-Critic on Zero-Sum Two-Player Stochastic Games. ICML 2021: 3899-3909 - [c75]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 - [c74]Ying Jin, Zhuoran Yang, Zhaoran Wang:
Is Pessimism Provably Efficient for Offline RL? ICML 2021: 5084-5096 - [c73]Lewis Liu, Yufeng Zhang, Zhuoran Yang, Reza Babanezhad, Zhaoran Wang:
Infinite-Dimensional Optimization for Zero-Sum Games via Variational Transport. ICML 2021: 7033-7044 - [c72]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 - [c71]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 - [c70]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 - [c69]Qiaomin Xie, Zhuoran Yang, Zhaoran Wang, Andreea Minca:
Learning While Playing in Mean-Field Games: Convergence and Optimality. ICML 2021: 11436-11447 - [c68]Tengyu Xu, Zhuoran Yang, Zhaoran Wang, Yingbin Liang:
Doubly Robust Off-Policy Actor-Critic: Convergence and Optimality. ICML 2021: 11581-11591 - [c67]Jingwei Zhang, Zhuoran Yang, Zhengyuan Zhou, Zhaoran Wang:
Provably Sample Efficient Reinforcement Learning in Competitive Linear Quadratic Systems. L4DC 2021: 597-598 - [c66]Boyi Liu, Qi Cai, Zhuoran Yang, Zhaoran Wang:
BooVI: Provably Efficient Bootstrapped Value Iteration. NeurIPS 2021: 7041-7053 - [c65]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 - [c64]Chenjia Bai, Lingxiao Wang, Lei Han, Animesh Garg, Jianye Hao, Peng Liu, Zhaoran Wang:
Dynamic Bottleneck for Robust Self-Supervised Exploration. NeurIPS 2021: 17007-17020 - [c63]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 - [c62]Yingjie Fei, Zhuoran Yang, Yudong Chen, Zhaoran Wang:
Exponential Bellman Equation and Improved Regret Bounds for Risk-Sensitive Reinforcement Learning. NeurIPS 2021: 20436-20446 - [c61]Lingxiao Wang, Zhuoran Yang, Zhaoran Wang:
Provably Efficient Causal Reinforcement Learning with Confounded Observational Data. NeurIPS 2021: 21164-21175 - [c60]Runzhe Wu, Yufeng Zhang, Zhuoran Yang, Zhaoran Wang:
Offline Constrained Multi-Objective Reinforcement Learning via Pessimistic Dual Value Iteration. NeurIPS 2021: 25439-25451 - [c59]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 - [i85]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) - [i84]Luofeng Liao, Zuyue Fu, Zhuoran Yang, Mladen Kolar, Zhaoran Wang:
Instrumental Variable Value Iteration for Causal Offline Reinforcement Learning. CoRR abs/2102.09907 (2021) - [i83]Tengyu Xu, Zhuoran Yang, Zhaoran Wang, Yingbin Liang:
Doubly Robust Off-Policy Actor-Critic: Convergence and Optimality. CoRR abs/2102.11866 (2021) - [i82]Yixuan Wang, Chao Huang, Zhilu Wang, Shichao Xu, Zhaoran Wang, Qi Zhu:
Cocktail: Learn a Better Neural Network Controller from Multiple Experts via Adaptive Mixing and Robust Distillation. CoRR abs/2103.05046 (2021) - [i81]Chenjia Bai, Lingxiao Wang, Lei Han, Jianye Hao, Animesh Garg, Peng Liu, Zhaoran Wang:
Principled Exploration via Optimistic Bootstrapping and Backward Induction. CoRR abs/2105.06022 (2021) - [i80]Yan Li, Lingxiao Wang, Jiachen Yang, Ethan Wang, Zhaoran Wang, Tuo Zhao, Hongyuan Zha:
Permutation Invariant Policy Optimization for Mean-Field Multi-Agent Reinforcement Learning: A Principled Approach. CoRR abs/2105.08268 (2021) - [i79]Yixuan Wang, Chao Huang, Zhaoran Wang, Zhilu Wang, Qi Zhu:
Verification in the Loop: Correct-by-Construction Control Learning with Reach-avoid Guarantees. CoRR abs/2106.03245 (2021) - [i78]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) - [i77]Zehao Dou, Zhuoran Yang, Zhaoran Wang, Simon S. Du:
Gap-Dependent Bounds for Two-Player Markov Games. CoRR abs/2107.00685 (2021) - [i76]Tengyu Xu, Zhuoran Yang, Zhaoran Wang, Yingbin Liang:
A Unified Off-Policy Evaluation Approach for General Value Function. CoRR abs/2107.02711 (2021) - [i75]Baihe Huang, Jason D. Lee, Zhaoran Wang, Zhuoran Yang:
Towards General Function Approximation in Zero-Sum Markov Games. CoRR abs/2107.14702 (2021) - [i74]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) - [i73]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) - [i72]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) - [i71]Han Zhong, Zhuoran Yang, Zhaoran Wang, Csaba Szepesvári:
Optimistic Policy Optimization is Provably Efficient in Non-stationary MDPs. CoRR abs/2110.08984 (2021) - [i70]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) - [i69]Chenjia Bai, Lingxiao Wang, Lei Han, Animesh Garg, Jianye Hao, Peng Liu, Zhaoran Wang:
Dynamic Bottleneck for Robust Self-Supervised Exploration. CoRR abs/2110.10735 (2021) - [i68]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) - [i67]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) - [i66]Zechu Li, Xiao-Yang Liu, Jiahao Zheng, Zhaoran Wang, Anwar Walid, Jian Guo:
FinRL-Podracer: High Performance and Scalable Deep Reinforcement Learning for Quantitative Finance. CoRR abs/2111.05188 (2021) - [i65]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) - [i64]Xiao-Yang Liu, Jingyang Rui, Jiechao Gao, Liuqing Yang, Hongyang Yang, Zhaoran Wang, Christina Dan Wang, Jian Guo:
FinRL-Meta: A Universe of Near-Real Market Environments for Data-Driven Deep Reinforcement Learning in Quantitative Finance. CoRR abs/2112.06753 (2021) - [i63]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) - [i62]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) - [i61]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
- [j6]Matey Neykov, Zhaoran Wang, Han Liu:
Agnostic Estimation for Phase Retrieval. J. Mach. Learn. Res. 21: 121:1-121:39 (2020) - [j5]Xiang Lyu, Will Wei Sun, Zhaoran Wang, Han Liu, Jian Yang, Guang Cheng:
Tensor Graphical Model: Non-Convex Optimization and Statistical Inference. IEEE Trans. Pattern Anal. Mach. Intell. 42(8): 2024-2037 (2020) - [c58]Chi Jin, Zhuoran Yang, Zhaoran Wang, Michael I. Jordan:
Provably efficient reinforcement learning with linear function approximation. COLT 2020: 2137-2143 - [c57]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 - [c56]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 - [c55]Zuyue Fu, Zhuoran Yang, Yongxin Chen, Zhaoran Wang:
Actor-Critic Provably Finds Nash Equilibria of Linear-Quadratic Mean-Field Games. ICLR 2020 - [c54]Lingxiao Wang, Qi Cai, Zhuoran Yang, Zhaoran Wang:
Neural Policy Gradient Methods: Global Optimality and Rates of Convergence. ICLR 2020 - [c53]Qi Cai, Zhuoran Yang, Chi Jin, Zhaoran Wang:
Provably Efficient Exploration in Policy Optimization. ICML 2020: 1283-1294 - [c52]Ying Jin, Zhaoran Wang, Junwei Lu:
Computational and Statistical Tradeoffs in Inferring Combinatorial Structures of Ising Model. ICML 2020: 4901-4910 - [c51]Sen Na, Yuwei Luo, Zhuoran Yang, Zhaoran Wang, Mladen Kolar:
Semiparametric Nonlinear Bipartite Graph Representation Learning with Provable Guarantees. ICML 2020: 7141-7152 - [c50]Qianli Shen, Yan Li, Haoming Jiang, Zhaoran Wang, Tuo Zhao:
Deep Reinforcement Learning with Robust and Smooth Policy. ICML 2020: 8707-8718 - [c49]Lingxiao Wang, Qi Cai, Zhuoran Yang, Zhaoran Wang:
On the Global Optimality of Model-Agnostic Meta-Learning. ICML 2020: 9837-9846 - [c48]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 - [c47]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 - [c46]Jianqing Fan, Zhaoran Wang, Yuchen Xie, Zhuoran Yang:
A Theoretical Analysis of Deep Q-Learning. L4DC 2020: 486-489 - [c45]Yingjie Fei, Zhuoran Yang, Yudong Chen, Zhaoran Wang, Qiaomin Xie:
Risk-Sensitive Reinforcement Learning: Near-Optimal Risk-Sample Tradeoff in Regret. NeurIPS 2020 - [c44]Yingjie Fei, Zhuoran Yang, Zhaoran Wang, Qiaomin Xie:
Dynamic Regret of Policy Optimization in Non-Stationary Environments. NeurIPS 2020 - [c43]Wanxin Jin, Zhaoran Wang, Zhuoran Yang, Shaoshuai Mou:
Pontryagin Differentiable Programming: An End-to-End Learning and Control Framework. NeurIPS 2020 - [c42]Jiayang Li, Jing Yu, Yu Marco Nie, Zhaoran Wang:
End-to-End Learning and Intervention in Games. NeurIPS 2020 - [c41]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 - [c40]Shuang Qiu, Xiaohan Wei, Zhuoran Yang, Jieping Ye, Zhaoran Wang:
Upper Confidence Primal-Dual Reinforcement Learning for CMDP with Adversarial Loss. NeurIPS 2020 - [c39]Hoi-To Wai, Zhuoran Yang, Zhaoran Wang, Mingyi Hong:
Provably Efficient Neural GTD for Off-Policy Learning. NeurIPS 2020 - [c38]Zhuoran Yang, Chi Jin, Zhaoran Wang, Mengdi Wang, Michael I. Jordan:
Provably Efficient Reinforcement Learning with Kernel and Neural Function Approximations. NeurIPS 2020 - [c37]Yufeng Zhang, Qi Cai, Zhuoran Yang, Yongxin Chen, Zhaoran Wang:
Can Temporal-Difference and Q-Learning Learn Representation? A Mean-Field Theory. NeurIPS 2020 - [i60]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) - [i59]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) - [i58]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) - [i57]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) - [i56]Sen Na, Yuwei Luo, Zhuoran Yang, Zhaoran Wang, Mladen Kolar:
Semiparametric Nonlinear Bipartite Graph Representation Learning with Provable Guarantees. CoRR abs/2003.01013 (2020) - [i55]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) - [i54]Qianli Shen, Yan Li, Haoming Jiang, Zhaoran Wang, Tuo Zhao:
Deep Reinforcement Learning with Smooth Policy. CoRR abs/2003.09534 (2020) - [i53]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) - [i52]Wanxin Jin, Zhaoran Wang, Zhuoran Yang, Shaoshuai Mou:
Neural Certificates for Safe Control Policies. CoRR abs/2006.08465 (2020) - [i51]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) - [i50]Lingxiao Wang, Zhuoran Yang, Zhaoran Wang:
Provably Efficient Causal Reinforcement Learning with Confounded Observational Data. CoRR abs/2006.12311 (2020) - [i49]Lingxiao Wang, Qi Cai, Zhuoran Yang, Zhaoran Wang:
On the Global Optimality of Model-Agnostic Meta-Learning. CoRR abs/2006.13182 (2020) - [i48]Yingjie Fei, Zhuoran Yang, Yudong Chen, Zhaoran Wang, Qiaomin Xie:
Risk-Sensitive Reinforcement Learning: Near-Optimal Risk-Sample Tradeoff in Regret. CoRR abs/2006.13827 (2020) - [i47]Yingjie Fei, Zhuoran Yang, Zhaoran Wang, Qiaomin Xie:
Dynamic Regret of Policy Optimization in Non-stationary Environments. CoRR abs/2007.00148 (2020) - [i46]Luofeng Liao, You-Lin Chen, Zhuoran Yang, Bo Dai, Zhaoran Wang, Mladen Kolar:
Provably Efficient Neural Estimation of Structural Equation Model: An Adversarial Approach. CoRR abs/2007.01290 (2020) - [i45]Yi Chen, Jinglin Chen, Jing Dong, Jian Peng, Zhaoran Wang:
Accelerating Nonconvex Learning via Replica Exchange Langevin Diffusion. CoRR abs/2007.01990 (2020) - [i44]Mingyi Hong, Hoi-To Wai, Zhaoran Wang, Zhuoran Yang:
A Two-Timescale Framework for Bilevel Optimization: Complexity Analysis and Application to Actor-Critic. CoRR abs/2007.05170 (2020) - [i43]Zuyue Fu, Zhuoran Yang, Zhaoran Wang:
Single-Timescale Actor-Critic Provably Finds Globally Optimal Policy. CoRR abs/2008.00483 (2020) - [i42]Shuang Qiu, Zhuoran Yang, Xiaohan Wei, Jieping Ye, Zhaoran Wang:
Single-Timescale Stochastic Nonconvex-Concave Optimization for Smooth Nonlinear TD Learning. CoRR abs/2008.10103 (2020) - [i41]Yining Wang, Yi Chen, Ethan X. Fang, Zhaoran Wang, Runze Li:
Nearly Dimension-Independent Sparse Linear Bandit over Small Action Spaces via Best Subset Selection. CoRR abs/2009.02003 (2020) - [i40]Qiaomin Xie, Zhuoran Yang, Zhaoran Wang, Andreea Minca:
Provable Fictitious Play for General Mean-Field Games. CoRR abs/2010.04211 (2020) - [i39]Chenjia Bai, Peng Liu, Zhaoran Wang, Kaiyu Liu, Lingxiao Wang, Yingnan Zhao:
Variational Dynamic for Self-Supervised Exploration in Deep Reinforcement Learning. CoRR abs/2010.08755 (2020) - [i38]Jiayang Li, Jing Yu, Yu Marco Nie, Zhaoran Wang:
End-to-End Learning and Intervention in Games. CoRR abs/2010.13834 (2020) - [i37]Zhuoran Yang, Chi Jin, Zhaoran Wang, Mengdi Wang, Michael I. Jordan:
Bridging Exploration and General Function Approximation in Reinforcement Learning: Provably Efficient Kernel and Neural Value Iterations. CoRR abs/2011.04622 (2020) - [i36]Zhuoran Yang, Yufeng Zhang, Yongxin Chen, Zhaoran Wang:
Variational Transport: A Convergent Particle-BasedAlgorithm for Distributional Optimization. CoRR abs/2012.11554 (2020) - [i35]Han Zhong, Ethan X. Fang, Zhuoran Yang, Zhaoran Wang:
Risk-Sensitive Deep RL: Variance-Constrained Actor-Critic Provably Finds Globally Optimal Policy. CoRR abs/2012.14098 (2020) - [i34]Ying Jin, Zhuoran Yang, Zhaoran Wang:
Is Pessimism Provably Efficient for Offline RL? CoRR abs/2012.15085 (2020) - [i33]You-Lin Chen, Zhaoran Wang, Mladen Kolar:
Provably Training Neural Network Classifiers under Fairness Constraints. CoRR abs/2012.15274 (2020)
2010 – 2019
- 2019
- [j4]Sen Na, Zhuoran Yang, Zhaoran Wang, Mladen Kolar:
High-dimensional Varying Index Coefficient Models via Stein's Identity. J. Mach. Learn. Res. 20: 152:1-152:44 (2019) - [j3]Zhuoran Yang, Lin F. Yang, Ethan X. Fang, Tuo Zhao, Zhaoran Wang, Matey Neykov:
Misspecified nonconvex statistical optimization for sparse phase retrieval. Math. Program. 176(1-2): 545-571 (2019) - [j2]Xingguo Li, Junwei Lu, Raman Arora, Jarvis D. Haupt, Han Liu, Zhaoran Wang, Tuo Zhao:
Symmetry, Saddle Points, and Global Optimization Landscape of Nonconvex Matrix Factorization. IEEE Trans. Inf. Theory 65(6): 3489-3514 (2019) - [c36]Yixuan Lin, Kaiqing Zhang, Zhuoran Yang, Zhaoran Wang, Tamer Basar, Romeil Sandhu, Ji Liu:
A Communication-Efficient Multi-Agent Actor-Critic Algorithm for Distributed Reinforcement Learning. CDC 2019: 5562-5567 - [c35]Kejun Huang, Zhuoran Yang, Zhaoran Wang, Mingyi Hong:
Learning Partially Observable Markov Decision Processes Using Coupled Canonical Polyadic Decomposition. DSW 2019: 295-299 - [c34]Yi Chen, Jinglin Chen, Jing Dong, Jian Peng, Zhaoran Wang:
Accelerating Nonconvex Learning via Replica Exchange Langevin diffusion. ICLR (Poster) 2019 - [c33]Yuan Xie, Boyi Liu, Qiang Liu, Zhaoran Wang, Yuan Zhou, Jian Peng:
Off-Policy Evaluation and Learning from Logged Bandit Feedback: Error Reduction via Surrogate Policy. ICLR (Poster) 2019 - [c32]Xiaohan Wei, Zhuoran Yang, Zhaoran Wang:
On the statistical rate of nonlinear recovery in generative models with heavy-tailed data. ICML 2019: 6697-6706 - [c31]Ming Yu, Zhuoran Yang, Mladen Kolar, Zhaoran Wang:
Convergent Policy Optimization for Safe Reinforcement Learning. NeurIPS 2019: 3121-3133 - [c30]Hoi-To Wai, Mingyi Hong, Zhuoran Yang, Zhaoran Wang, Kexin Tang:
Variance Reduced Policy Evaluation with Smooth Function Approximation. NeurIPS 2019: 5776-5787 - [c29]Zhuoran Yang, Yongxin Chen, Mingyi Hong, Zhaoran Wang:
Provably Global Convergence of Actor-Critic: A Case for Linear Quadratic Regulator with Ergodic Cost. NeurIPS 2019: 8351-8363 - [c28]Lingxiao Wang, Zhuoran Yang, Zhaoran Wang:
Statistical-Computational Tradeoff in Single Index Models. NeurIPS 2019: 10419-10426 - [c27]Boyi Liu, Qi Cai, Zhuoran Yang, Zhaoran Wang:
Neural Trust Region/Proximal Policy Optimization Attains Globally Optimal Policy. NeurIPS 2019: 10564-10575 - [c26]Qi Cai, Zhuoran Yang, Jason D. Lee, Zhaoran Wang:
Neural Temporal-Difference Learning Converges to Global Optima. NeurIPS 2019: 11312-11322 - [i32]Zhuoran Yang, Yuchen Xie, Zhaoran Wang:
A Theoretical Analysis of Deep Q-Learning. CoRR abs/1901.00137 (2019) - [i31]Qi Cai, Mingyi Hong, Yongxin Chen, Zhaoran Wang:
On the Global Convergence of Imitation Learning: A Case for Linear Quadratic Regulator. CoRR abs/1901.03674 (2019) - [i30]Wesley Suttle, Zhuoran Yang, Kaiqing Zhang, Zhaoran Wang, Tamer Basar, Ji Liu:
A Multi-Agent Off-Policy Actor-Critic Algorithm for Distributed Reinforcement Learning. CoRR abs/1903.06372 (2019) - [i29]Qi Cai, Zhuoran Yang, Jason D. Lee, Zhaoran Wang:
Neural Temporal-Difference Learning Converges to Global Optima. CoRR abs/1905.10027 (2019) - [i28]Boyi Liu, Qi Cai, Zhuoran Yang, Zhaoran Wang:
Neural Proximal/Trust Region Policy Optimization Attains Globally Optimal Policy. CoRR abs/1906.10306 (2019) - [i27]Yixuan Lin, Kaiqing Zhang, Zhuoran Yang, Zhaoran Wang, Tamer Basar, Romeil Sandhu, Ji Liu:
A Communication-Efficient Multi-Agent Actor-Critic Algorithm for Distributed Reinforcement Learning. CoRR abs/1907.03053 (2019) - [i26]Chi Jin, Zhuoran Yang, Zhaoran Wang, Michael I. Jordan:
Provably Efficient Reinforcement Learning with Linear Function Approximation. CoRR abs/1907.05388 (2019) - [i25]Zhuoran Yang, Yongxin Chen, Mingyi Hong, Zhaoran Wang:
On the Global Convergence of Actor-Critic: A Case for Linear Quadratic Regulator with Ergodic Cost. CoRR abs/1907.06246 (2019) - [i24]Xinyang Yi, Zhaoran Wang, Zhuoran Yang, Constantine Caramanis, Han Liu:
More Supervision, Less Computation: Statistical-Computational Tradeoffs in Weakly Supervised Learning. CoRR abs/1907.06257 (2019) - [i23]Dongsheng Ding, Xiaohan Wei, Zhuoran Yang, Zhaoran Wang, Mihailo R. Jovanovic:
Fast Multi-Agent Temporal-Difference Learning via Homotopy Stochastic Primal-Dual Optimization. CoRR abs/1908.02805 (2019) - [i22]Lingxiao Wang, Qi Cai, Zhuoran Yang, Zhaoran Wang:
Neural Policy Gradient Methods: Global Optimality and Rates of Convergence. CoRR abs/1909.01150 (2019) - [i21]Yang Liu, Zuyue Fu, Zhuoran Yang, Zhaoran Wang:
Credible Sample Elicitation by Deep Learning, for Deep Learning. CoRR abs/1910.03155 (2019) - [i20]Zuyue Fu, Zhuoran Yang, Yongxin Chen, Zhaoran Wang:
Actor-Critic Provably Finds Nash Equilibria of Linear-Quadratic Mean-Field Games. CoRR abs/1910.07498 (2019) - [i19]Ming Yu, Zhuoran Yang, Mladen Kolar, Zhaoran Wang:
Convergent Policy Optimization for Safe Reinforcement Learning. CoRR abs/1910.12156 (2019) - [i18]Qi Cai, Zhuoran Yang, Chi Jin, Zhaoran Wang:
Provably Efficient Exploration in Policy Optimization. CoRR abs/1912.05830 (2019) - [i17]Yuwei Luo, Zhuoran Yang, Zhaoran Wang, Mladen Kolar:
Natural Actor-Critic Converges Globally for Hierarchical Linear Quadratic Regulator. CoRR abs/1912.06875 (2019) - [i16]Wanxin Jin, Zhaoran Wang, Zhuoran Yang, Shaoshuai Mou:
Pontryagin Differentiable Programming: An End-to-End Learning and Control Framework. CoRR abs/1912.12970 (2019) - 2018
- [b1]Zhaoran Wang:
Nonconvex Statistical Optimization. Princeton University, USA, 2018 - [c25]Kaiqing Zhang, Zhuoran Yang, Zhaoran Wang:
Nonlinear Structured Signal Estimation in High Dimensions via Iterative Hard Thresholding. AISTATS 2018: 258-268 - [c24]Jason Ge, Zhaoran Wang, Mengdi Wang, Han Liu:
Minimax-Optimal Privacy-Preserving Sparse PCA in Distributed Systems. AISTATS 2018: 1589-1598 - [c23]Shi Zhi, Fan Yang, Zheyi Zhu, Qi Li, Zhaoran Wang, Jiawei Han:
Dynamic Truth Discovery on Numerical Data. ICDM 2018: 817-826 - [c22]Hao Lu, Yuan Cao, Junwei Lu, Han Liu, Zhaoran Wang:
The Edge Density Barrier: Computational-Statistical Tradeoffs in Combinatorial Inference. ICML 2018: 3253-3262 - [c21]Xingguo Li, Jarvis D. Haupt, Junwei Lu, Zhaoran Wang, Raman Arora, Han Liu, Tuo Zhao:
Symmetry. Saddle Points, and Global Optimization Landscape of Nonconvex Matrix Factorization. ITA 2018: 1-9 - [c20]Ming Yu, Zhuoran Yang, Tuo Zhao, Mladen Kolar, Zhaoran Wang:
Provable Gaussian Embedding with One Observation. NeurIPS 2018: 6765-6775 - [c19]Hoi-To Wai, Zhuoran Yang, Zhaoran Wang, Mingyi Hong:
Multi-Agent Reinforcement Learning via Double Averaging Primal-Dual Optimization. NeurIPS 2018: 9672-9683 - [c18]Yi Chen, Zhuoran Yang, Yuchen Xie, Zhaoran Wang:
Contrastive Learning from Pairwise Measurements. NeurIPS 2018: 10932-10941 - [i15]Yingxiang Yang, Adams Wei Yu, Zhaoran Wang, Tuo Zhao:
Detecting Nonlinear Causality in Multivariate Time Series with Sparse Additive Models. CoRR abs/1803.03919 (2018) - [i14]Hoi-To Wai, Zhuoran Yang, Zhaoran Wang, Mingyi Hong:
Multi-Agent Reinforcement Learning via Double Averaging Primal-Dual Optimization. CoRR abs/1806.00877 (2018) - [i13]Xingguo Li, Junwei Lu, Zhaoran Wang, Jarvis D. Haupt, Tuo Zhao:
On Tighter Generalization Bound for Deep Neural Networks: CNNs, ResNets, and Beyond. CoRR abs/1806.05159 (2018) - [i12]Yuan Xie, Boyi Liu, Qiang Liu, Zhaoran Wang, Yuan Zhou, Jian Peng:
Off-Policy Evaluation and Learning from Logged Bandit Feedback: Error Reduction via Surrogate Policy. CoRR abs/1808.00232 (2018) - [i11]Jianqing Fan, Han Liu, Zhaoran Wang, Zhuoran Yang:
Curse of Heterogeneity: Computational Barriers in Sparse Mixture Models and Phase Retrieval. CoRR abs/1808.06996 (2018) - [i10]Chris Junchi Li, Zhaoran Wang, Han Liu:
Online ICA: Understanding Global Dynamics of Nonconvex Optimization via Diffusion Processes. CoRR abs/1808.09642 (2018) - [i9]Kean Ming Tan, Zhaoran Wang, Tong Zhang, Han Liu, R. Dennis Cook:
A convex formulation for high-dimensional sparse sliced inverse regression. CoRR abs/1809.06024 (2018) - [i8]Sen Na, Zhuoran Yang, Zhaoran Wang, Mladen Kolar:
High-dimensional Varying Index Coefficient Models via Stein's Identity. CoRR abs/1810.07128 (2018) - [i7]Ming Yu, Zhuoran Yang, Tuo Zhao, Mladen Kolar, Zhaoran Wang:
Provable Gaussian Embedding with One Observation. CoRR abs/1810.11098 (2018) - 2017
- [c17]Zhuoran Yang, Krishnakumar Balasubramanian, Zhaoran Wang, Han Liu:
Estimating High-dimensional Non-Gaussian Multiple Index Models via Stein's Lemma. NIPS 2017: 6097-6106 - [i6]Zhuoran Yang, Lin F. Yang, Ethan X. Fang, Tuo Zhao, Zhaoran Wang, Matey Neykov:
Misspecified Nonconvex Statistical Optimization for Phase Retrieval. CoRR abs/1712.06245 (2017) - 2016
- [c16]Quanquan Gu, Zhaoran Wang, Han Liu:
Low-Rank and Sparse Structure Pursuit via Alternating Minimization. AISTATS 2016: 600-609 - [c15]Zhaoran Wang, Quanquan Gu, Han Liu:
On the Statistical Limits of Convex Relaxations. ICML 2016: 1368-1377 - [c14]Zhuoran Yang, Zhaoran Wang, Han Liu, Yonina C. Eldar, Tong Zhang:
Sparse Nonlinear Regression: Parameter Estimation under Nonconvexity. ICML 2016: 2472-2481 - [c13]Houping Xiao, Jing Gao, Zhaoran Wang, Shiyu Wang, Lu Su, Han Liu:
A Truth Discovery Approach with Theoretical Guarantee. KDD 2016: 1925-1934 - [c12]Alex Beatson, Zhaoran Wang, Han Liu:
Blind Attacks on Machine Learners. NIPS 2016: 2397-2405 - [c11]Davood Hajinezhad, Mingyi Hong, Tuo Zhao, Zhaoran Wang:
NESTT: A Nonconvex Primal-Dual Splitting Method for Distributed and Stochastic Optimization. NIPS 2016: 3207-3215 - [c10]Matey Neykov, Zhaoran Wang, Han Liu:
Agnostic Estimation for Misspecified Phase Retrieval Models. NIPS 2016: 4089-4097 - [c9]Xinyang Yi, Zhaoran Wang, Zhuoran Yang, Constantine Caramanis, Han Liu:
More Supervision, Less Computation: Statistical-Computational Tradeoffs in Weakly Supervised Learning. NIPS 2016: 4475-4483 - [c8]Chris Junchi Li, Zhaoran Wang, Han Liu:
Online ICA: Understanding Global Dynamics of Nonconvex Optimization via Diffusion Processes. NIPS 2016: 4961-4969 - [i5]Davood Hajinezhad, Mingyi Hong, Tuo Zhao, Zhaoran Wang:
NESTT: A Nonconvex Primal-Dual Splitting Method for Distributed and Stochastic Optimization. CoRR abs/1605.07747 (2016) - [i4]Xingguo Li, Zhaoran Wang, Junwei Lu, Raman Arora, Jarvis D. Haupt, Han Liu, Tuo Zhao:
Symmetry, Saddle Points, and Global Geometry of Nonconvex Matrix Factorization. CoRR abs/1612.09296 (2016) - 2015
- [c7]Tuo Zhao, Zhaoran Wang, Han Liu:
A Nonconvex Optimization Framework for Low Rank Matrix Estimation. NIPS 2015: 559-567 - [c6]Wei Sun, Zhaoran Wang, Han Liu, Guang Cheng:
Non-convex Statistical Optimization for Sparse Tensor Graphical Model. NIPS 2015: 1081-1089 - [c5]Xinyang Yi, Zhaoran Wang, Constantine Caramanis, Han Liu:
Optimal Linear Estimation under Unknown Nonlinear Transform. NIPS 2015: 1549-1557 - [c4]Zhaoran Wang, Quanquan Gu, Yang Ning, Han Liu:
High Dimensional EM Algorithm: Statistical Optimization and Asymptotic Normality. NIPS 2015: 2521-2529 - [i3]Xinyang Yi, Zhaoran Wang, Constantine Caramanis, Han Liu:
Optimal linear estimation under unknown nonlinear transform. CoRR abs/1505.03257 (2015) - [i2]Zhuoran Yang, Zhaoran Wang, Han Liu, Yonina C. Eldar, Tong Zhang:
Sparse Nonlinear Regression: Parameter Estimation and Asymptotic Inference. CoRR abs/1511.04514 (2015) - 2014
- [j1]Bingsheng He, Han Liu, Zhaoran Wang, Xiaoming Yuan:
A Strictly Contractive Peaceman-Rachford Splitting Method for Convex Programming. SIAM J. Optim. 24(3): 1011-1040 (2014) - [c3]Quanquan Gu, Zhaoran Wang, Han Liu:
Sparse PCA with Oracle Property. NIPS 2014: 1529-1537 - [c2]Zhaoran Wang, Huanran Lu, Han Liu:
Tighten after Relax: Minimax-Optimal Sparse PCA in Polynomial Time. NIPS 2014: 3383-3391 - [i1]Zhaoran Wang, Huanran Lu, Han Liu:
Nonconvex Statistical Optimization: Minimax-Optimal Sparse PCA in Polynomial Time. CoRR abs/1408.5352 (2014) - 2013
- [c1]Zhaoran Wang, Fang Han, Han Liu:
Sparse Principal Component Analysis for High Dimensional Multivariate Time Series. AISTATS 2013: 48-56
Coauthor Index
[j19] [j18] [c128] [c125] [c124] [i149] [i145] [i136] [j15] [j14] [j13] [j12] [j11] [c123] [c121] [c120] [c119] [c117] [c116] [c114] [c112] [c111] [c110] [c109] [c107] [i133] [i132] [i131] [i128] [i127] [i126] [i125] [i124] [i123] [i121] [i119] [i118] [i117] [i114] [i113] [c106] [c104] [c103] [c102] [c101] [c100] [c99] [c98] [c97] [c96] [c95] [c94] [c93] [c92] [c90] [c89] [c87] [c86] [c85] [i111] [i110] [i109] [i108] [i107] [i106] [i105] [i104] [i103] [i102] [i101] [i98] [i97] [i95] [i94] [i93] [i92] [i91] [i89] [i88] [i87] [j8] [c84] [c83] [c82] [c79] [c77] [c76] [c75] [c74] [c73] [c72] [c71] [c70] [c69] [c68] [c67] [c66] [c65] [c63] [c62] [c61] [c60] [c59] [i85] [i84] [i83] [i78] [i77] [i76] [i75] [i74] [i73] [i72] [i71] [i70] [i68] [i67] [i65] [i63] [i62] [i61] [c58] [c57] [c56] [c55] [c54] [c53] [c51] [c49] [c48] [c47] [c46] [c45] [c44] [c43] [c41] [c40] [c39] [c38] [c37] [i60] [i59] [i58] [i57] [i56] [i55] [i53] [i52] [i51] [i50] [i49] [i48] [i47] [i46] [i44] [i43] [i42] [i40] [i37] [i36] [i35] [i34] [j4] [j3] [c36] [c35] [c32] [c31] [c30] [c29] [c28] [c27] [c26] [i32] [i30] [i29] [i28] [i27] [i26] [i25] [i24] [i23] [i22] [i21] [i20] [i19] [i18] [i17] [i16] [c25] [c20] [c19] [c18] [i14] [i11] [i8] [i7] [c17] [i6] [c14] [c9] [i2]
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