Sparse Principal Component Analysis for High Dimensional Multivariate Time Series. - Zhaoran Wang 001; Fang Han; Han Liu 001 (AISTATS, 2013)

Sparse PCA with Oracle Property. - Quanquan Gu; Zhaoran Wang 001; Han Liu 001 (NIPS, 2014)

Tighten after Relax: Minimax-Optimal Sparse PCA in Polynomial Time. - Zhaoran Wang 001; Huanran Lu; Han Liu 001 (NIPS, 2014)

Nonconvex Statistical Optimization: Minimax-Optimal Sparse PCA in Polynomial Time. - Zhaoran Wang 001; Huanran Lu; Han Liu 001 (CoRR, 2014)

A Strictly Contractive Peaceman-Rachford Splitting Method for Convex Programming. - Bingsheng He; Han Liu 001; Zhaoran Wang 001; Xiaoming Yuan 001 (SIAM J. Optim., 2014)

Non-convex Statistical Optimization for Sparse Tensor Graphical Model. - Wei Sun 027; Zhaoran Wang 001; Han Liu 001; Guang Cheng 003 (NIPS, 2015)

High Dimensional EM Algorithm: Statistical Optimization and Asymptotic Normality. - Zhaoran Wang 001; Quanquan Gu; Yang Ning; Han Liu 001 (NIPS, 2015)

Optimal Linear Estimation under Unknown Nonlinear Transform. - Xinyang Yi; Zhaoran Wang 001; Constantine Caramanis; Han Liu 001 (NIPS, 2015)

A Nonconvex Optimization Framework for Low Rank Matrix Estimation. - Tuo Zhao; Zhaoran Wang 001; Han Liu 001 (NIPS, 2015)

Sparse Nonlinear Regression: Parameter Estimation and Asymptotic Inference. - Zhuoran Yang; Zhaoran Wang 001; Han Liu 001; Yonina C. Eldar; Tong Zhang 001 (CoRR, 2015)

Low-Rank and Sparse Structure Pursuit via Alternating Minimization. - Quanquan Gu; Zhaoran Wang 001; Han Liu 001 (AISTATS, 2016)

On the Statistical Limits of Convex Relaxations. - Zhaoran Wang 001; Quanquan Gu; Han Liu 001 (ICML, 2016)

Sparse Nonlinear Regression: Parameter Estimation under Nonconvexity. - Zhuoran Yang; Zhaoran Wang 001; Han Liu 001; Yonina C. Eldar; Tong Zhang 001 (ICML, 2016)

A Truth Discovery Approach with Theoretical Guarantee. - Houping Xiao; Jing Gao 004; Zhaoran Wang 001; Shiyu Wang; Lu Su 001; Han Liu 001 (KDD, 2016)

Blind Attacks on Machine Learners. - Alex Beatson; Zhaoran Wang 001; Han Liu 001 (NIPS, 2016)

NESTT: A Nonconvex Primal-Dual Splitting Method for Distributed and Stochastic Optimization. - Davood Hajinezhad; Mingyi Hong 001; Tuo Zhao; Zhaoran Wang 001 (NIPS, 2016)

Online ICA: Understanding Global Dynamics of Nonconvex Optimization via Diffusion Processes. - Chris Junchi Li; Zhaoran Wang 001; Han Liu 001 (NIPS, 2016)

Agnostic Estimation for Misspecified Phase Retrieval Models. - Matey Neykov; Zhaoran Wang 001; Han Liu 001 (NIPS, 2016)

More Supervision, Less Computation: Statistical-Computational Tradeoffs in Weakly Supervised Learning. - Xinyang Yi; Zhaoran Wang 001; Zhuoran Yang; Constantine Caramanis; Han Liu 001 (NIPS, 2016)

Symmetry, Saddle Points, and Global Geometry of Nonconvex Matrix Factorization. - Xingguo Li; Zhaoran Wang 001; Junwei Lu; Raman Arora; Jarvis D. Haupt; Han Liu 001; Tuo Zhao (CoRR, 2016)

Estimating High-dimensional Non-Gaussian Multiple Index Models via Stein's Lemma. - Zhuoran Yang; Krishnakumar Balasubramanian 002; Zhaoran Wang 001; Han Liu 001 (NIPS, 2017)

Misspecified Nonconvex Statistical Optimization for Phase Retrieval. - Zhuoran Yang; Lin F. Yang; Ethan X. Fang; Tuo Zhao; Zhaoran Wang 001; Matey Neykov (CoRR, 2017)

Minimax-Optimal Privacy-Preserving Sparse PCA in Distributed Systems. - Jason Ge; Zhaoran Wang 001; Mengdi Wang; Han Liu 001 (AISTATS, 2018)

Nonlinear Structured Signal Estimation in High Dimensions via Iterative Hard Thresholding. - Kaiqing Zhang; Zhuoran Yang; Zhaoran Wang 001 (AISTATS, 2018)

Dynamic Truth Discovery on Numerical Data. - Shi Zhi; Fan Yang 084; Zheyi Zhu; Qi Li 012; Zhaoran Wang 001; Jiawei Han 001 (ICDM, 2018)

The Edge Density Barrier: Computational-Statistical Tradeoffs in Combinatorial Inference. - Hao Lu; Yuan Cao 006; Junwei Lu; Han Liu 001; Zhaoran Wang 001 (ICML, 2018)

Contrastive Learning from Pairwise Measurements. - Yi Chen; Zhuoran Yang; Yuchen Xie; Zhaoran Wang 001 (NeurIPS, 2018)

Multi-Agent Reinforcement Learning via Double Averaging Primal-Dual Optimization. - Hoi-To Wai; Zhuoran Yang; Zhaoran Wang 001; Mingyi Hong 001 (NeurIPS, 2018)

Provable Gaussian Embedding with One Observation. - Ming Yu 005; Zhuoran Yang; Tuo Zhao; Mladen Kolar; Zhaoran Wang 001 (NeurIPS, 2018)

Detecting Nonlinear Causality in Multivariate Time Series with Sparse Additive Models. - Yingxiang Yang; Adams Wei Yu; Zhaoran Wang 001; Tuo Zhao (CoRR, 2018)

On Tighter Generalization Bound for Deep Neural Networks: CNNs, ResNets, and Beyond. - Xingguo Li; Junwei Lu; Zhaoran Wang 001; Jarvis D. Haupt; Tuo Zhao (CoRR, 2018)

Curse of Heterogeneity: Computational Barriers in Sparse Mixture Models and Phase Retrieval. - Jianqing Fan; Han Liu 001; Zhaoran Wang 001; Zhuoran Yang (CoRR, 2018)

A convex formulation for high-dimensional sparse sliced inverse regression. - Kean Ming Tan; Zhaoran Wang 001; Tong Zhang 001; Han Liu 001; R. Dennis Cook (CoRR, 2018)

Nonconvex Statistical Optimization - Zhaoran Wang 001 (2018)

A Communication-Efficient Multi-Agent Actor-Critic Algorithm for Distributed Reinforcement Learning. - Yixuan Lin; Kaiqing Zhang; Zhuoran Yang; Zhaoran Wang 001; Tamer Basar; Romeil Sandhu; Ji Liu 001 (CDC, 2019)

Learning Partially Observable Markov Decision Processes Using Coupled Canonical Polyadic Decomposition. - Kejun Huang; Zhuoran Yang; Zhaoran Wang 001; Mingyi Hong 001 (DSW, 2019)

Accelerating Nonconvex Learning via Replica Exchange Langevin diffusion. - Yi Chen; Jinglin Chen; Jing Dong 007; Jian Peng 001; Zhaoran Wang 001 (ICLR (Poster), 2019)

Off-Policy Evaluation and Learning from Logged Bandit Feedback: Error Reduction via Surrogate Policy. - Yuan Xie 005; Boyi Liu 001; Qiang Liu 001; Zhaoran Wang 001; Yuan Zhou 007; Jian Peng 001 (ICLR (Poster), 2019)

On the statistical rate of nonlinear recovery in generative models with heavy-tailed data. - Xiaohan Wei; Zhuoran Yang; Zhaoran Wang 001 (ICML, 2019)

Neural Temporal-Difference Learning Converges to Global Optima. - Qi Cai; Zhuoran Yang; Jason D. Lee; Zhaoran Wang 001 (NeurIPS, 2019)

Neural Trust Region/Proximal Policy Optimization Attains Globally Optimal Policy. - Boyi Liu 001; Qi Cai; Zhuoran Yang; Zhaoran Wang 001 (NeurIPS, 2019)

Variance Reduced Policy Evaluation with Smooth Function Approximation. - Hoi-To Wai; Mingyi Hong 001; Zhuoran Yang; Zhaoran Wang 001; Kexin Tang (NeurIPS, 2019)

Statistical-Computational Tradeoff in Single Index Models. - Lingxiao Wang 003; Zhuoran Yang; Zhaoran Wang 001 (NeurIPS, 2019)

Provably Global Convergence of Actor-Critic: A Case for Linear Quadratic Regulator with Ergodic Cost. - Zhuoran Yang; Yongxin Chen; Mingyi Hong 001; Zhaoran Wang 001 (NeurIPS, 2019)

Convergent Policy Optimization for Safe Reinforcement Learning. - Ming Yu 005; Zhuoran Yang; Mladen Kolar; Zhaoran Wang 001 (NeurIPS, 2019)

A Theoretical Analysis of Deep Q-Learning. - Zhuoran Yang; Yuchen Xie; Zhaoran Wang 001 (CoRR, 2019)

On the Global Convergence of Imitation Learning: A Case for Linear Quadratic Regulator. - Qi Cai; Mingyi Hong 001; Yongxin Chen; Zhaoran Wang 001 (CoRR, 2019)

A Multi-Agent Off-Policy Actor-Critic Algorithm for Distributed Reinforcement Learning. - Wesley Suttle; Zhuoran Yang; Kaiqing Zhang; Zhaoran Wang 001; Tamer Basar; Ji Liu 001 (CoRR, 2019)

Neural Proximal/Trust Region Policy Optimization Attains Globally Optimal Policy. - Boyi Liu 001; Qi Cai; Zhuoran Yang; Zhaoran Wang 001 (CoRR, 2019)

On the Global Convergence of Actor-Critic: A Case for Linear Quadratic Regulator with Ergodic Cost. - Zhuoran Yang; Yongxin Chen; Mingyi Hong 001; Zhaoran Wang 001 (CoRR, 2019)

Fast Multi-Agent Temporal-Difference Learning via Homotopy Stochastic Primal-Dual Optimization. - Dongsheng Ding; Xiaohan Wei; Zhuoran Yang; Zhaoran Wang 001; Mihailo R. Jovanovic (CoRR, 2019)

Credible Sample Elicitation by Deep Learning, for Deep Learning. - Yang Liu 018; Zuyue Fu; Zhuoran Yang; Zhaoran Wang 001 (CoRR, 2019)

Natural Actor-Critic Converges Globally for Hierarchical Linear Quadratic Regulator. - Yuwei Luo; Zhuoran Yang; Zhaoran Wang 001; Mladen Kolar (CoRR, 2019)

High-dimensional Varying Index Coefficient Models via Stein's Identity. - Sen Na; Zhuoran Yang; Zhaoran Wang 001; Mladen Kolar (J. Mach. Learn. Res., 2019)

Misspecified nonconvex statistical optimization for sparse phase retrieval. - Zhuoran Yang; Lin F. Yang; Ethan X. Fang; Tuo Zhao; Zhaoran Wang 001; Matey Neykov (Math. Program., 2019)

Symmetry, Saddle Points, and Global Optimization Landscape of Nonconvex Matrix Factorization. - Xingguo Li; Junwei Lu; Raman Arora; Jarvis D. Haupt; Han Liu 001; Zhaoran Wang 001; Tuo Zhao (IEEE Trans. Inf. Theory, 2019)

On Computation and Generalization of Generative Adversarial Imitation Learning. - Minshuo Chen; Yizhou Wang 006; Tianyi Liu; Zhuoran Yang; Xingguo Li; Zhaoran Wang 001; Tuo Zhao (ICLR, 2020)

Actor-Critic Provably Finds Nash Equilibria of Linear-Quadratic Mean-Field Games. - Zuyue Fu; Zhuoran Yang; Yongxin Chen; Zhaoran Wang 001 (ICLR, 2020)

Neural Policy Gradient Methods: Global Optimality and Rates of Convergence. - Lingxiao Wang 003; Qi Cai; Zhuoran Yang; Zhaoran Wang 001 (ICLR, 2020)

Provably Efficient Exploration in Policy Optimization. - Qi Cai; Zhuoran Yang; Chi Jin 001; Zhaoran Wang 001 (ICML, 2020)

Computational and Statistical Tradeoffs in Inferring Combinatorial Structures of Ising Model. - Ying Jin; Zhaoran Wang 001; Junwei Lu (ICML, 2020)

Semiparametric Nonlinear Bipartite Graph Representation Learning with Provable Guarantees. - Sen Na; Yuwei Luo; Zhuoran Yang; Zhaoran Wang 001; Mladen Kolar (ICML, 2020)

Deep Reinforcement Learning with Robust and Smooth Policy. - Qianli Shen; Yan Li 074; Haoming Jiang; Zhaoran Wang 001; Tuo Zhao (ICML, 2020)

On the Global Optimality of Model-Agnostic Meta-Learning. - Lingxiao Wang 003; Qi Cai; Zhuoran Yang; Zhaoran Wang 001 (ICML, 2020)

Breaking the Curse of Many Agents: Provable Mean Embedding Q-Iteration for Mean-Field Reinforcement Learning. - Lingxiao Wang 003; Zhuoran Yang; Zhaoran Wang 001 (ICML, 2020)

Generative Adversarial Imitation Learning with Neural Network Parameterization: Global Optimality and Convergence Rate. - Yufeng Zhang 007; Qi Cai; Zhuoran Yang; Zhaoran Wang 001 (ICML, 2020)

A Theoretical Analysis of Deep Q-Learning. - Jianqing Fan; Zhaoran Wang 001; Yuchen Xie; Zhuoran Yang (L4DC, 2020)

Risk-Sensitive Reinforcement Learning: Near-Optimal Risk-Sample Tradeoff in Regret. - Yingjie Fei; Zhuoran Yang; Yudong Chen 001; Zhaoran Wang 001; Qiaomin Xie (NeurIPS, 2020)

Dynamic Regret of Policy Optimization in Non-Stationary Environments. - Yingjie Fei; Zhuoran Yang; Zhaoran Wang 001; Qiaomin Xie (NeurIPS, 2020)

Pontryagin Differentiable Programming: An End-to-End Learning and Control Framework. - Wanxin Jin; Zhaoran Wang 001; Zhuoran Yang; Shaoshuai Mou (NeurIPS, 2020)

End-to-End Learning and Intervention in Games. - Jiayang Li 001; Jing Yu; Yu Marco Nie; Zhaoran Wang 001 (NeurIPS, 2020)

Provably Efficient Neural Estimation of Structural Equation Models: An Adversarial Approach. - Luofeng Liao; You-Lin Chen; Zhuoran Yang; Bo Dai 001; Mladen Kolar; Zhaoran Wang 001 (NeurIPS, 2020)

Upper Confidence Primal-Dual Reinforcement Learning for CMDP with Adversarial Loss. - Shuang Qiu; Xiaohan Wei; Zhuoran Yang; Jieping Ye; Zhaoran Wang 001 (NeurIPS, 2020)

Provably Efficient Neural GTD for Off-Policy Learning. - Hoi-To Wai; Zhuoran Yang; Zhaoran Wang 001; Mingyi Hong 001 (NeurIPS, 2020)

Provably Efficient Reinforcement Learning with Kernel and Neural Function Approximations. - Zhuoran Yang; Chi Jin 001; Zhaoran Wang 001; Mengdi Wang; Michael I. Jordan (NeurIPS, 2020)

Can Temporal-Difference and Q-Learning Learn Representation? A Mean-Field Theory. - Yufeng Zhang 007; Qi Cai; Zhuoran Yang; Yongxin Chen; Zhaoran Wang 001 (NeurIPS, 2020)

Upper Confidence Primal-Dual Optimization: Stochastically Constrained Markov Decision Processes with Adversarial Losses and Unknown Transitions. - Shuang Qiu; Xiaohan Wei; Zhuoran Yang; Jieping Ye; Zhaoran Wang 001 (CoRR, 2020)

Generative Adversarial Imitation Learning with Neural Networks: Global Optimality and Convergence Rate. - Yufeng Zhang 007; Qi Cai; Zhuoran Yang; Zhaoran Wang 001 (CoRR, 2020)

Deep Reinforcement Learning with Smooth Policy. - Qianli Shen; Yan Li 074; Haoming Jiang; Zhaoran Wang 001; Tuo Zhao (CoRR, 2020)

Neural Certificates for Safe Control Policies. - Wanxin Jin; Zhaoran Wang 001; Zhuoran Yang; Shaoshuai Mou (CoRR, 2020)

Provably Efficient Neural Estimation of Structural Equation Model: An Adversarial Approach. - Luofeng Liao; You-Lin Chen; Zhuoran Yang; Bo Dai 001; Zhaoran Wang 001; Mladen Kolar (CoRR, 2020)

A Two-Timescale Framework for Bilevel Optimization: Complexity Analysis and Application to Actor-Critic. - Mingyi Hong 001; Hoi-To Wai; Zhaoran Wang 001; Zhuoran Yang (CoRR, 2020)

Single-Timescale Stochastic Nonconvex-Concave Optimization for Smooth Nonlinear TD Learning. - Shuang Qiu; Zhuoran Yang; Xiaohan Wei; Jieping Ye; Zhaoran Wang 001 (CoRR, 2020)

Nearly Dimension-Independent Sparse Linear Bandit over Small Action Spaces via Best Subset Selection. - Yining Wang; Yi Chen; Ethan X. Fang; Zhaoran Wang 001; Runze Li (CoRR, 2020)

Provable Fictitious Play for General Mean-Field Games. - Qiaomin Xie; Zhuoran Yang; Zhaoran Wang 001; Andreea Minca (CoRR, 2020)

Variational Dynamic for Self-Supervised Exploration in Deep Reinforcement Learning. - Chenjia Bai; Peng Liu 008; Zhaoran Wang 001; Kaiyu Liu; Lingxiao Wang 003; Yingnan Zhao 002 (CoRR, 2020)

Bridging Exploration and General Function Approximation in Reinforcement Learning: Provably Efficient Kernel and Neural Value Iterations. - Zhuoran Yang; Chi Jin 001; Zhaoran Wang 001; Mengdi Wang; Michael I. Jordan (CoRR, 2020)

Variational Transport: A Convergent Particle-BasedAlgorithm for Distributional Optimization. - Zhuoran Yang; Yufeng Zhang 007; Yongxin Chen; Zhaoran Wang 001 (CoRR, 2020)

Risk-Sensitive Deep RL: Variance-Constrained Actor-Critic Provably Finds Globally Optimal Policy. - Han Zhong 001; Ethan X. Fang; Zhuoran Yang; Zhaoran Wang 001 (CoRR, 2020)

Provably Training Neural Network Classifiers under Fairness Constraints. - You-Lin Chen; Zhaoran Wang 001; Mladen Kolar (CoRR, 2020)

Agnostic Estimation for Phase Retrieval. - Matey Neykov; Zhaoran Wang 001; Han Liu 001 (J. Mach. Learn. Res., 2020)

Tensor Graphical Model: Non-Convex Optimization and Statistical Inference. - Xiang Lyu; Will Wei Sun; Zhaoran Wang 001; Han Liu 001; Jian Yang 002; Guang Cheng 003 (IEEE Trans. Pattern Anal. Mach. Intell., 2020)

Provably Efficient Safe Exploration via Primal-Dual Policy Optimization. - Dongsheng Ding; Xiaohan Wei; Zhuoran Yang; Zhaoran Wang 001; Mihailo R. Jovanovic (AISTATS, 2021)

Sample Elicitation. - Jiaheng Wei; Zuyue Fu; Yang Liu 018; Xingyu Li; Zhuoran Yang; Zhaoran Wang 001 (AISTATS, 2021)

Provably Efficient Actor-Critic for Risk-Sensitive and Robust Adversarial RL: A Linear-Quadratic Case. - Yufeng Zhang 007; Zhuoran Yang; Zhaoran Wang 001 (AISTATS, 2021)

Cocktail: Learn a Better Neural Network Controller from Multiple Experts via Adaptive Mixing and Robust Distillation. - Yixuan Wang 001; Chao Huang 015; Zhilu Wang; Shichao Xu; Zhaoran Wang 001; Qi Zhu 002 (DAC, 2021)

FinRL-podracer: high performance and scalable deep reinforcement learning for quantitative finance. - Zechu Li; Xiao-Yang Liu; Jiahao Zheng 002; Zhaoran Wang 001; Anwar Walid; Jian Guo (ICAIF, 2021)

Single-Timescale Actor-Critic Provably Finds Globally Optimal Policy. - Zuyue Fu; Zhuoran Yang; Zhaoran Wang 001 (ICLR, 2021)

Principled Exploration via Optimistic Bootstrapping and Backward Induction. - Chenjia Bai; Lingxiao Wang 003; Lei Han 001; Jianye Hao; Animesh Garg; Peng Liu 008; Zhaoran Wang 001 (ICML, 2021)

Risk-Sensitive Reinforcement Learning with Function Approximation: A Debiasing Approach. - Yingjie Fei; Zhuoran Yang; Zhaoran Wang 001 (ICML, 2021)

Decentralized Single-Timescale Actor-Critic on Zero-Sum Two-Player Stochastic Games. - Hongyi Guo; Zuyue Fu; Zhuoran Yang; Zhaoran Wang 001 (ICML, 2021)

Randomized Exploration in Reinforcement Learning with General Value Function Approximation. - Haque Ishfaq; Qiwen Cui; Viet Nguyen; Alex Ayoub; Zhuoran Yang; Zhaoran Wang 001; Doina Precup; Lin Yang 011 (ICML, 2021)

Is Pessimism Provably Efficient for Offline RL? - Ying Jin; Zhuoran Yang; Zhaoran Wang 001 (ICML, 2021)

Infinite-Dimensional Optimization for Zero-Sum Games via Variational Transport. - Lewis Liu; Yufeng Zhang 007; Zhuoran Yang; Reza Babanezhad 001; Zhaoran Wang 001 (ICML, 2021)

Provably Efficient Fictitious Play Policy Optimization for Zero-Sum Markov Games with Structured Transitions. - Shuang Qiu; Xiaohan Wei; Jieping Ye; Zhaoran Wang 001; Zhuoran Yang (ICML, 2021)

On Reward-Free RL with Kernel and Neural Function Approximations: Single-Agent MDP and Markov Game. - Shuang Qiu; Jieping Ye; Zhaoran Wang 001; Zhuoran Yang (ICML, 2021)

Global Convergence of Policy Gradient for Linear-Quadratic Mean-Field Control/Game in Continuous Time. - Weichen Wang; Jiequn Han; Zhuoran Yang; Zhaoran Wang 001 (ICML, 2021)

Learning While Playing in Mean-Field Games: Convergence and Optimality. - Qiaomin Xie; Zhuoran Yang; Zhaoran Wang 001; Andreea Minca (ICML, 2021)

Doubly Robust Off-Policy Actor-Critic: Convergence and Optimality. - Tengyu Xu; Zhuoran Yang; Zhaoran Wang 001; Yingbin Liang (ICML, 2021)

Provably Sample Efficient Reinforcement Learning in Competitive Linear Quadratic Systems. - Jingwei Zhang; Zhuoran Yang; Zhengyuan Zhou; Zhaoran Wang 001 (L4DC, 2021)

Dynamic Bottleneck for Robust Self-Supervised Exploration. - Chenjia Bai; Lingxiao Wang 003; Lei Han 001; Animesh Garg; Jianye Hao; Peng Liu 008; Zhaoran Wang 001 (NeurIPS, 2021)

Pessimism Meets Invariance: Provably Efficient Offline Mean-Field Multi-Agent RL. - Minshuo Chen; Yan Li 074; Ethan Wang; Zhuoran Yang; Zhaoran Wang 001; Tuo Zhao (NeurIPS, 2021)

Exponential Bellman Equation and Improved Regret Bounds for Risk-Sensitive Reinforcement Learning. - Yingjie Fei; Zhuoran Yang; Yudong Chen 001; Zhaoran Wang 001 (NeurIPS, 2021)

A Near-Optimal Algorithm for Stochastic Bilevel Optimization via Double-Momentum. - Prashant Khanduri; Siliang Zeng; Mingyi Hong 001; Hoi-To Wai; Zhaoran Wang 001; Zhuoran Yang (NeurIPS, 2021)

BooVI: Provably Efficient Bootstrapped Value Iteration. - Boyi Liu 001; Qi Cai; Zhuoran Yang; Zhaoran Wang 001 (NeurIPS, 2021)

Provably Efficient Causal Reinforcement Learning with Confounded Observational Data. - Lingxiao Wang 003; Zhuoran Yang; Zhaoran Wang 001 (NeurIPS, 2021)

Offline Constrained Multi-Objective Reinforcement Learning via Pessimistic Dual Value Iteration. - Runzhe Wu; Yufeng Zhang 007; Zhuoran Yang; Zhaoran Wang 001 (NeurIPS, 2021)

Wasserstein Flow Meets Replicator Dynamics: A Mean-Field Analysis of Representation Learning in Actor-Critic. - Yufeng Zhang 007; Siyu Chen 001; Zhuoran Yang; Michael I. Jordan; Zhaoran Wang 001 (NeurIPS, 2021)

A Momentum-Assisted Single-Timescale Stochastic Approximation Algorithm for Bilevel Optimization. - Prashant Khanduri; Siliang Zeng; Mingyi Hong 001; Hoi-To Wai; Zhaoran Wang 001; Zhuoran Yang (CoRR, 2021)

Instrumental Variable Value Iteration for Causal Offline Reinforcement Learning. - Luofeng Liao; Zuyue Fu; Zhuoran Yang; Mladen Kolar; Zhaoran Wang 001 (CoRR, 2021)

Permutation Invariant Policy Optimization for Mean-Field Multi-Agent Reinforcement Learning: A Principled Approach. - Yan Li 074; Lingxiao Wang 003; Jiachen Yang; Ethan Wang; Zhaoran Wang 001; Tuo Zhao; Hongyuan Zha (CoRR, 2021)

Verification in the Loop: Correct-by-Construction Control Learning with Reach-avoid Guarantees. - Yixuan Wang 001; Chao Huang 015; Zhaoran Wang 001; Zhilu Wang; Qi Zhu 002 (CoRR, 2021)

A Unified Off-Policy Evaluation Approach for General Value Function. - Tengyu Xu; Zhuoran Yang; Zhaoran Wang 001; Yingbin Liang (CoRR, 2021)

Online Bootstrap Inference For Policy Evaluation in Reinforcement Learning. - Pratik Ramprasad; Yuantong Li; Zhuoran Yang; Zhaoran Wang 001; Will Wei Sun; Guang Cheng 003 (CoRR, 2021)

Provably Efficient Generative Adversarial Imitation Learning for Online and Offline Setting with Linear Function Approximation. - Zhihan Liu; Yufeng Zhang 007; Zuyue Fu; Zhuoran Yang; Zhaoran Wang 001 (CoRR, 2021)

Inducing Equilibria via Incentives: Simultaneous Design-and-Play Finds Global Optima. - Boyi Liu 001; Jiayang Li 001; Zhuoran Yang; Hoi-To Wai; Mingyi Hong 001; Yu Marco Nie; Zhaoran Wang 001 (CoRR, 2021)

Optimistic Policy Optimization is Provably Efficient in Non-stationary MDPs. - Han Zhong 001; Zhuoran Yang; Zhaoran Wang 001; Csaba Szepesvári (CoRR, 2021)

SCORE: Spurious COrrelation REduction for Offline Reinforcement Learning. - Zhihong Deng 002; Zuyue Fu; Lingxiao Wang 003; Zhuoran Yang; Chenjia Bai; Zhaoran Wang 001; Jing Jiang 002 (CoRR, 2021)

ElegantRL-Podracer: Scalable and Elastic Library for Cloud-Native Deep Reinforcement Learning. - Xiao-Yang Liu; Zechu Li; Zhuoran Yang; Jiahao Zheng 002; Zhaoran Wang 001; Anwar Walid; Jian Guo; Michael I. Jordan (CoRR, 2021)

FinRL-Meta: A Universe of Near-Real Market Environments for Data-Driven Deep Reinforcement Learning in Quantitative Finance. - Xiao-Yang Liu; Jingyang Rui; Jiechao Gao; Liuqing Yang; Hongyang Yang; Zhaoran Wang 001; Christina Dan Wang; Jian Guo (CoRR, 2021)

Can Reinforcement Learning Find Stackelberg-Nash Equilibria in General-Sum Markov Games with Myopic Followers? - Han Zhong 001; Zhuoran Yang; Zhaoran Wang 001; Michael I. Jordan (CoRR, 2021)

Exponential Family Model-Based Reinforcement Learning via Score Matching. - Gene Li; Junbo Li 003; Nathan Srebro; Zhaoran Wang 001; Zhuoran Yang (CoRR, 2021)

On Finite-Time Convergence of Actor-Critic Algorithm. - Shuang Qiu; Zhuoran Yang; Jieping Ye; Zhaoran Wang 001 (IEEE J. Sel. Areas Inf. Theory, 2021)

Spectrum Truncation Power Iteration for Agnostic Matrix Phase Retrieval. - Lewis Liu; Songtao Lu; Tuo Zhao; Zhaoran Wang 001 (IEEE Trans. Signal Process., 2021)

Gap-Dependent Bounds for Two-Player Markov Games. - Zehao Dou; Zhuoran Yang; Zhaoran Wang 001; Simon S. Du (AISTATS, 2022)

Design-while-verify: correct-by-construction control learning with verification in the loop. - Yixuan Wang 001; Chao Huang 015; Zhaoran Wang 001; Zhilu Wang; Qi Zhu 002 (DAC, 2022)

Pessimistic Bootstrapping for Uncertainty-Driven Offline Reinforcement Learning. - Chenjia Bai; Lingxiao Wang 003; Zhuoran Yang; Zhi-Hong Deng 002; Animesh Garg; Peng Liu 008; Zhaoran Wang 001 (ICLR, 2022)

Towards General Function Approximation in Zero-Sum Markov Games. - Baihe Huang; Jason D. Lee; Zhaoran Wang 001; Zhuoran Yang (ICLR, 2022)

Reinforcement Learning from Partial Observation: Linear Function Approximation with Provable Sample Efficiency. - Qi Cai; Zhuoran Yang; Zhaoran Wang 001 (ICML, 2022)

Adaptive Model Design for Markov Decision Process. - Siyu Chen 001; Donglin Yang; Jiayang Li 001; Senmiao Wang; Zhuoran Yang; Zhaoran Wang 001 (ICML, 2022)

Human-in-the-loop: Provably Efficient Preference-based Reinforcement Learning with General Function Approximation. - Xiaoyu Chen 008; Han Zhong 001; Zhuoran Yang; Zhaoran Wang 001; Liwei Wang 001 (ICML, 2022)

Provably Efficient Offline Reinforcement Learning for Partially Observable Markov Decision Processes. - Hongyi Guo; Qi Cai; Yufeng Zhang 007; Zhuoran Yang; Zhaoran Wang 001 (ICML, 2022)

Welfare Maximization in Competitive Equilibrium: Reinforcement Learning for Markov Exchange Economy. - Zhihan Liu; Miao Lu; Zhaoran Wang 001; Michael I. Jordan; Zhuoran Yang (ICML, 2022)

Learning from Demonstration: Provably Efficient Adversarial Policy Imitation with Linear Function Approximation. - Zhihan Liu; Yufeng Zhang 007; Zuyue Fu; Zhuoran Yang; Zhaoran Wang 001 (ICML, 2022)

Pessimism meets VCG: Learning Dynamic Mechanism Design via Offline Reinforcement Learning. - Boxiang Lyu; Zhaoran Wang 001; Mladen Kolar; Zhuoran Yang (ICML, 2022)

Contrastive UCB: Provably Efficient Contrastive Self-Supervised Learning in Online Reinforcement Learning. - Shuang Qiu; Lingxiao Wang 003; Chenjia Bai; Zhuoran Yang; Zhaoran Wang 001 (ICML, 2022)

Pessimistic Minimax Value Iteration: Provably Efficient Equilibrium Learning from Offline Datasets. - Han Zhong 001; Wei Xiong 015; Jiyuan Tan; Liwei Wang 001; Tong Zhang 001; Zhaoran Wang 001; Zhuoran Yang (ICML, 2022)

Exponential Family Model-Based Reinforcement Learning via Score Matching. - Gene Li; Junbo Li 003; Anmol Kabra; Nati Srebro; Zhaoran Wang 001; Zhuoran Yang (NeurIPS, 2022)

Inducing Equilibria via Incentives: Simultaneous Design-and-Play Ensures Global Convergence. - Boyi Liu 001; Jiayang Li 001; Zhuoran Yang; Hoi-To Wai; Mingyi Hong 001; Yu Marco Nie; Zhaoran Wang 001 (NeurIPS, 2022)

FinRL-Meta: Market Environments and Benchmarks for Data-Driven Financial Reinforcement Learning. - Xiao-Yang Liu; Ziyi Xia; Jingyang Rui; Jiechao Gao; Hongyang Yang; Ming Zhu 002; Christina Dan Wang; Zhaoran Wang 001; Jian Guo (NeurIPS, 2022)

Learn to Match with No Regret: Reinforcement Learning in Markov Matching Markets. - Yifei Min; Tianhao Wang 002; Ruitu Xu; Zhaoran Wang 001; Michael I. Jordan; Zhuoran Yang (NeurIPS, 2022)

A Unifying Framework of Off-Policy General Value Function Evaluation. - Tengyu Xu; Zhuoran Yang; Zhaoran Wang 001; Yingbin Liang (NeurIPS, 2022)

RORL: Robust Offline Reinforcement Learning via Conservative Smoothing. - Rui Yang 010; Chenjia Bai; Xiaoteng Ma; Zhaoran Wang 001; Chongjie Zhang; Lei Han 001 (NeurIPS, 2022)

Relational Reasoning via Set Transformers: Provable Efficiency and Applications to MARL. - Fengzhuo Zhang; Boyi Liu 001; Kaixin Wang; Vincent Y. F. Tan; Zhuoran Yang; Zhaoran Wang 001 (NeurIPS, 2022)

Accelerate online reinforcement learning for building HVAC control with heterogeneous expert guidances. - Shichao Xu; Yangyang Fu; Yixuan Wang 001; Zhuoran Yang; Zheng O'Neill; Zhaoran Wang 001; Qi Zhu 002 (BuildSys, 2022)

Sequential Information Design: Markov Persuasion Process and Its Efficient Reinforcement Learning. - Jibang Wu; Zixuan Zhang; Zhe Feng 004; Zhaoran Wang 001; Zhuoran Yang; Michael I. Jordan; Haifeng Xu (EC, 2022)

Joint Differentiable Optimization and Verification for Certified Reinforcement Learning. - Yixuan Wang 001; Chao Huang 015; Zhaoran Wang 001; Zhuoran Yang; Qi Zhu 002 (CoRR, 2022)

Learning Dynamic Mechanisms in Unknown Environments: A Reinforcement Learning Approach. - Boxiang Lyu; Qinglin Meng; Shuang Qiu; Zhaoran Wang 001; Zhuoran Yang; Michael I. Jordan (CoRR, 2022)

Sample-Efficient Reinforcement Learning for POMDPs with Linear Function Approximations. - Qi Cai; Zhuoran Yang; Zhaoran Wang 001 (CoRR, 2022)

Embed to Control Partially Observed Systems: Representation Learning with Provable Sample Efficiency. - Lingxiao Wang 003; Qi Cai; Zhuoran Yang; Zhaoran Wang 001 (CoRR, 2022)

Federated Offline Reinforcement Learning. - Doudou Zhou; Yufeng Zhang 007; Aaron Sonabend W.; Zhaoran Wang 001; Junwei Lu; Tianxi Cai (CoRR, 2022)

Differentiable Bilevel Programming for Stackelberg Congestion Games. - Jiayang Li 001; Jing Yu; Qianni Wang; Boyi Liu 001; Zhaoran Wang 001; Yu Marco Nie (CoRR, 2022)

Offline Reinforcement Learning with Instrumental Variables in Confounded Markov Decision Processes. - Zuyue Fu; Zhengling Qi; Zhaoran Wang 001; Zhuoran Yang; Yanxun Xu; Michael R. Kosorok (CoRR, 2022)

A Reinforcement Learning Approach in Multi-Phase Second-Price Auction Design. - Rui Ai 002; Boxiang Lyu; Zhaoran Wang 001; Zhuoran Yang; Michael I. Jordan (CoRR, 2022)

GEC: A Unified Framework for Interactive Decision Making in MDP, POMDP, and Beyond. - Han Zhong 001; Wei Xiong 015; Sirui Zheng; Liwei Wang 001; Zhaoran Wang 001; Zhuoran Yang; Tong Zhang 001 (CoRR, 2022)

Policy learning "without" overlap: Pessimism and generalized empirical Bernstein's inequality. - Ying Jin; Zhimei Ren; Zhuoran Yang; Zhaoran Wang 001 (CoRR, 2022)

Offline Reinforcement Learning for Human-Guided Human-Machine Interaction with Private Information. - Zuyue Fu; Zhengling Qi; Zhuoran Yang; Zhaoran Wang 001; Lan Wang (CoRR, 2022)

Offline Policy Optimization in RL with Variance Regularizaton. - Riashat Islam; Samarth Sinha; Homanga Bharadhwaj; Samin Yeasar Arnob; Zhuoran Yang; Animesh Garg; Zhaoran Wang 001; Lihong Li; Doina Precup (CoRR, 2022)

An Analysis of Attention via the Lens of Exchangeability and Latent Variable Models. - Yufeng Zhang 007; Boyi Liu 001; Qi Cai; Lingxiao Wang 003; Zhaoran Wang 001 (CoRR, 2022)

Finding Regularized Competitive Equilibria of Heterogeneous Agent Macroeconomic Models via Reinforcement Learning. - Ruitu Xu; Yifei Min; Tianhao Wang 002; Michael I. Jordan; Zhaoran Wang 001; Zhuoran Yang (AISTATS, 2023)

Differentiable Arbitrating in Zero-sum Markov Games. - Jing Wang; Meichen Song; Feng Gao; Boyi Liu 001; Zhaoran Wang 001; Yi Wu 013 (AAMAS, 2023)

Joint Differentiable Optimization and Verification for Certified Reinforcement Learning. - Yixuan Wang 001; Simon Sinong Zhan; Zhilu Wang; Chao Huang 015; Zhaoran Wang 001; Zhuoran Yang; Qi Zhu 002 (ICCPS, 2023)

Represent to Control Partially Observed Systems: Representation Learning with Provable Sample Efficiency. - Lingxiao Wang 003; Qi Cai; Zhuoran Yang; Zhaoran Wang 001 (ICLR, 2023)

Pessimism in the Face of Confounders: Provably Efficient Offline Reinforcement Learning in Partially Observable Markov Decision Processes. - Miao Lu; Yifei Min; Zhaoran Wang 001; Zhuoran Yang (ICLR, 2023)

Latent Variable Representation for Reinforcement Learning. - Tongzheng Ren; Chenjun Xiao; Tianjun Zhang; Na Li 002; Zhaoran Wang 001; Sujay Sanghavi; Dale Schuurmans; Bo Dai 001 (ICLR, 2023)

Offline RL with No OOD Actions: In-Sample Learning via Implicit Value Regularization. - Haoran Xu 003; Li Jiang 008; Jianxiong Li; Zhuoran Yang; Zhaoran Wang 001; Wai Kin Victor Chan; Xianyuan Zhan (ICLR, 2023)

Optimistic Exploration with Learned Features Provably Solves Markov Decision Processes with Neural Dynamics. - Sirui Zheng; Lingxiao Wang 003; Shuang Qiu; Zuyue Fu; Zhuoran Yang; Csaba Szepesvári; Zhaoran Wang 001 (ICLR, 2023)

Enforcing Hard Constraints with Soft Barriers: Safe Reinforcement Learning in Unknown Stochastic Environments. - Yixuan Wang 001; Simon Sinong Zhan; Ruochen Jiao; Zhilu Wang; Wanxin Jin; Zhuoran Yang; Zhaoran Wang 001; Chao Huang 015; Qi Zhu 002 (ICML, 2023)

Local Optimization Achieves Global Optimality in Multi-Agent Reinforcement Learning. - Yulai Zhao 002; Zhuoran Yang; Zhaoran Wang 001; Jason D. Lee (ICML, 2023)

Achieving Hierarchy-Free Approximation for Bilevel Programs with Equilibrium Constraints. - Jiayang Li 001; Jing Yu; Boyi Liu 001; Yu Marco Nie; Zhaoran Wang 001 (ICML, 2023)

Adaptive Barrier Smoothing for First-Order Policy Gradient with Contact Dynamics. - Shenao Zhang; Wanxin Jin; Zhaoran Wang 001 (ICML, 2023)

Provably Efficient Generalized Lagrangian Policy Optimization for Safe Multi-Agent Reinforcement Learning. - Dongsheng Ding; Xiaohan Wei; Zhuoran Yang; Zhaoran Wang 001; Mihailo R. Jovanovic (L4DC, 2023)

Maximize to Explore: One Objective Function Fusing Estimation, Planning, and Exploration. - Zhihan Liu; Miao Lu; Wei Xiong 015; Han Zhong 001; Hao Hu; Shenao Zhang; Sirui Zheng; Zhuoran Yang; Zhaoran Wang 001 (NeurIPS, 2023)

Posterior Sampling for Competitive RL: Function Approximation and Partial Observation. - Shuang Qiu; Ziyu Dai; Han Zhong 001; Zhaoran Wang 001; Zhuoran Yang; Tong Zhang 001 (NeurIPS, 2023)

Model-Based Reparameterization Policy Gradient Methods: Theory and Practical Algorithms. - Shenao Zhang; Boyi Liu 001; Zhaoran Wang 001; Tuo Zhao (NeurIPS, 2023)

Learning Regularized Monotone Graphon Mean-Field Games. - Fengzhuo Zhang; Vincent Y. F. Tan; Zhaoran Wang 001; Zhuoran Yang (NeurIPS, 2023)

Finding Regularized Competitive Equilibria of Heterogeneous Agent Macroeconomic Models with Reinforcement Learning. - Ruitu Xu; Yifei Min; Tianhao Wang 002; Zhaoran Wang 001; Michael I. Jordan; Zhuoran Yang (CoRR, 2023)

A Unified Framework of Policy Learning for Contextual Bandit with Confounding Bias and Missing Observations. - Siyu Chen 001; Yitan Wang; Zhaoran Wang 001; Zhuoran Yang (CoRR, 2023)

One Objective to Rule Them All: A Maximization Objective Fusing Estimation and Planning for Exploration. - Zhihan Liu; Miao Lu; Wei Xiong 015; Han Zhong 001; Hao Hu; Shenao Zhang; Sirui Zheng; Zhuoran Yang; Zhaoran Wang 001 (CoRR, 2023)

Contextual Dynamic Pricing with Strategic Buyers. - Pangpang Liu; Zhuoran Yang; Zhaoran Wang 001; Will Wei Sun (CoRR, 2023)

Reason for Future, Act for Now: A Principled Framework for Autonomous LLM Agents with Provable Sample Efficiency. - Zhihan Liu; Hao Hu; Shenao Zhang; Hongyi Guo; Shuqi Ke; Boyi Liu 001; Zhaoran Wang 001 (CoRR, 2023)

Learning Regularized Graphon Mean-Field Games with Unknown Graphons. - Fengzhuo Zhang; Vincent Y. F. Tan; Zhaoran Wang 001; Zhuoran Yang (CoRR, 2023)

A Principled Framework for Knowledge-enhanced Large Language Model. - Saizhuo Wang; Zhihan Liu; Zhaoran Wang 001; Jian Guo (CoRR, 2023)

Provably Efficient High-Dimensional Bandit Learning with Batched Feedbacks. - Jianqing Fan; Zhaoran Wang 001; Zhuoran Yang; Chenlu Ye (CoRR, 2023)

Empowering Autonomous Driving with Large Language Models: A Safety Perspective. - Yixuan Wang 001; Ruochen Jiao; Chengtian Lang; Simon Sinong Zhan; Chao Huang 015; Zhaoran Wang 001; Zhuoran Yang; Qi Zhu 002 (CoRR, 2023)

Can Reinforcement Learning Find Stackelberg-Nash Equilibria in General-Sum Markov Games with Myopically Rational Followers? - Han Zhong 001; Zhuoran Yang; Zhaoran Wang 001; Michael I. Jordan (J. Mach. Learn. Res., 2023)

Double Duality: Variational Primal-Dual Policy Optimization for Constrained Reinforcement Learning. - Zihao Li; Boyi Liu 001; Zhuoran Yang; Zhaoran Wang 001; Mengdi Wang (J. Mach. Learn. Res., 2023)

Addressing Hindsight Bias in Multigoal Reinforcement Learning. - Chenjia Bai; Lingxiao Wang 003; Yixin Wang 002; Zhaoran Wang 001; Rui Zhao; Chenyao Bai; Peng Liu 008 (IEEE Trans. Cybern., 2023)

Learning Zero-Sum Simultaneous-Move Markov Games Using Function Approximation and Correlated Equilibrium. - Qiaomin Xie; Yudong Chen 001; Zhaoran Wang 001; Zhuoran Yang (Math. Oper. Res., 2023)

A Two-Timescale Stochastic Algorithm Framework for Bilevel Optimization: Complexity Analysis and Application to Actor-Critic. - Mingyi Hong 001; Hoi-To Wai; Zhaoran Wang 001; Zhuoran Yang (SIAM J. Optim., 2023)

Provably Efficient Reinforcement Learning with Linear Function Approximation. - Chi Jin 001; Zhuoran Yang; Zhaoran Wang 001; Michael I. Jordan (Math. Oper. Res., 2023)

Variational Dynamic for Self-Supervised Exploration in Deep Reinforcement Learning. - Chenjia Bai; Peng Liu 008; Kaiyu Liu; Lingxiao Wang 003; Yingnan Zhao 002; Lei Han 001; Zhaoran Wang 001 (IEEE Trans. Neural Networks Learn. Syst., 2023)

Let Models Speak Ciphers: Multiagent Debate through Embeddings. - Chau Pham 001; Boyi Liu 001; Yingxiang Yang; Zhengyu Chen 001; Tianyi Liu; Jianbo Yuan; Bryan A. Plummer; Zhaoran Wang 001; Hongxia Yang (ICLR, 2024)

Sample-Efficient Multi-Agent RL: An Optimization Perspective. - Nuoya Xiong; Zhihan Liu; Zhaoran Wang 001; Zhuoran Yang (ICLR, 2024)

Adaptive-Gradient Policy Optimization: Enhancing Policy Learning in Non-Smooth Differentiable Simulations. - Feng Gao; Liangzhi Shi; Shenao Zhang; Zhaoran Wang 001; Yi Wu 013 (ICML, 2024)

Reason for Future, Act for Now: A Principled Architecture for Autonomous LLM Agents. - Zhihan Liu; Hao Hu; Shenao Zhang; Hongyi Guo; Shuqi Ke; Boyi Liu 001; Zhaoran Wang 001 (ICML, 2024)

A General Framework for Sequential Decision-Making under Adaptivity Constraints. - Nuoya Xiong; Zhaoran Wang 001; Zhuoran Yang (ICML, 2024)

How Does Goal Relabeling Improve Sample Efficiency? - Sirui Zheng; Chenjia Bai; Zhuoran Yang; Zhaoran Wang 001 (ICML, 2024)

Provably Mitigating Overoptimization in RLHF: Your SFT Loss is Implicitly an Adversarial Regularizer. - Zhihan Liu; Miao Lu; Shenao Zhang; Boyi Liu 001; Hongyi Guo; Yingxiang Yang; Jose H. Blanchet; Zhaoran Wang 001 (NeurIPS, 2024)

Human-Instruction-Free LLM Self-Alignment with Limited Samples. - Hongyi Guo; Yuanshun Yao; Wei Shen; Jiaheng Wei; Xiaoying Zhang; Zhaoran Wang 001; Yang Liu 018 (CoRR, 2024)

How Can LLM Guide RL? A Value-Based Approach. - Shenao Zhang; Sirui Zheng; Shuqi Ke; Zhihan Liu; Wanxin Jin; Jianbo Yuan; Yingxiang Yang; Hongxia Yang; Zhaoran Wang 001 (CoRR, 2024)

Can Large Language Models Play Games? A Case Study of A Self-Play Approach. - Hongyi Guo; Zhihan Liu; Yufeng Zhang 007; Zhaoran Wang 001 (CoRR, 2024)

Advancing Object Goal Navigation Through LLM-enhanced Object Affinities Transfer. - Mengying Lin; Yaran Chen; Dongbin Zhao; Zhaoran Wang 001 (CoRR, 2024)

A Mean-Field Analysis of Neural Gradient Descent-Ascent: Applications to Functional Conditional Moment Equations. - Yuchen Zhu; Yufeng Zhang 007; Zhaoran Wang 001; Zhuoran Yang; Xiaohong Chen (CoRR, 2024)

Self-Exploring Language Models: Active Preference Elicitation for Online Alignment. - Shenao Zhang; Donghan Yu; Hiteshi Sharma; Ziyi Yang; Shuohang Wang; Hany Hassan; Zhaoran Wang 001 (CoRR, 2024)

Toward Optimal LLM Alignments Using Two-Player Games. - Rui Zheng; Hongyi Guo; Zhihan Liu; Xiaoying Zhang; Yuanshun Yao; Xiaojun Xu; Zhaoran Wang 001; Zhiheng Xi; Tao Gui; Qi Zhang 001; Xuanjing Huang 001; Hang Li 001; et al. (CoRR, 2024)

Safe MPC Alignment with Human Directional Feedback. - Zhixian Xie; Wenlong Zhang; Yi Ren; Zhaoran Wang 001; George J. Pappas; Wanxin Jin (CoRR, 2024)

Just say what you want: only-prompting self-rewarding online preference optimization. - Ruijie Xu 006; Zhihan Liu; Yongfei Liu; Shipeng Yan; Zhaoran Wang 001; Zhi Zhang; Xuming He 001 (CoRR, 2024)

Reward-Augmented Data Enhances Direct Preference Alignment of LLMs. - Shenao Zhang; Zhihan Liu; Boyi Liu 001; Yufeng Zhang 007; Yingxiang Yang; Yongfei Liu; Liyu Chen; Tao Sun; Zhaoran Wang 001 (CoRR, 2024)

Language-Model-Assisted Bi-Level Programming for Reward Learning from Internet Videos. - Harsh Mahesheka; Zhixian Xie; Zhaoran Wang 001; Wanxin Jin (CoRR, 2024)

DSTC: Direct Preference Learning with Only Self-Generated Tests and Code to Improve Code LMs. - Zhihan Liu; Shenao Zhang; Zhaoran Wang 001 (CoRR, 2024)

An Instrumental Value for Data Production and its Application to Data Pricing. - Rui Ai 002; Boxiang Lyu; Zhaoran Wang 001; Zhuoran Yang; Haifeng Xu (CoRR, 2024)

Hindsight Planner: A Closed-Loop Few-Shot Planner for Embodied Instruction Following. - Yuxiao Yang; Shenao Zhang; Zhihan Liu; Huaxiu Yao; Zhaoran Wang 001 (CoRR, 2024)

Neural Temporal Difference and Q Learning Provably Converge to Global Optima. - Qi Cai; Zhuoran Yang; Jason D. Lee; Zhaoran Wang 001 (Math. Oper. Res., 2024)

Wardrop Equilibrium Can Be Boundedly Rational: A New Behavioral Theory of Route Choice. - Jiayang Li 001; Zhaoran Wang 001; Yu Marco Nie (Transp. Sci., 2024)

False Correlation Reduction for Offline Reinforcement Learning. - Zhihong Deng 002; Zuyue Fu; Lingxiao Wang 003; Zhuoran Yang; Chenjia Bai; Tianyi Zhou 001; Zhaoran Wang 001; Jing Jiang 002 (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

Dynamic datasets and market environments for financial reinforcement learning. - Xiao-Yang Liu; Ziyi Xia; Hongyang Yang; Jiechao Gao; Daochen Zha; Ming Zhu 002; Christina Dan Wang; Zhaoran Wang 001; Jian Guo (Mach. Learn., 2024)

Monotonic Quantile Network for Worst-Case Offline Reinforcement Learning. - Chenjia Bai; Ting Xiao; Zhoufan Zhu; Lingxiao Wang 003; Fan Zhou; Animesh Garg; Bin He 003; Peng Liu 008; Zhaoran Wang 001 (IEEE Trans. Neural Networks Learn. Syst., 2024)

What and How does In-Context Learning Learn? Bayesian Model Averaging, Parameterization, and Generalization. - Yufeng Zhang 007; Fengzhuo Zhang; Zhuoran Yang; Zhaoran Wang 001 (AISTATS, 2025)

Are Transformers Able to Reason by Connecting Separated Knowledge in Training Data? - Yutong Yin; Zhaoran Wang 001 (ICLR, 2025)

Self-Exploring Language Models: Active Preference Elicitation for Online Alignment. - Shenao Zhang; Donghan Yu; Hiteshi Sharma; Han Zhong 001; Zhihan Liu; Ziyi Yang; Shuohang Wang; Hany Hassan Awadalla; Zhaoran Wang 001 (Trans. Mach. Learn. Res., 2025)

BRiTE: Bootstrapping Reinforced Thinking Process to Enhance Language Model Reasoning. - Han Zhong 001; Yutong Yin; Shenao Zhang; Xiaojun Xu; Yuanxin Liu; Yifei Zuo; Zhihan Liu; Boyi Liu 001; Sirui Zheng; Hongyi Guo; Liwei Wang 001; Mingyi Hong 001; et al. (CoRR, 2025)

Beyond Markovian: Reflective Exploration via Bayes-Adaptive RL for LLM Reasoning. - Shenao Zhang; Yaqing Wang; Yinxiao Liu; Tianqi Liu; Peter Grabowski; Eugene Ie; Zhaoran Wang 001; Yunxuan Li (CoRR, 2025)

The Sample Complexity of Online Strategic Decision Making with Information Asymmetry and Knowledge Transportability. - Jiachen Hu; Rui Ai 002; Han Zhong 001; Xiaoyu Chen 008; Liwei Wang 001; Zhaoran Wang 001; Zhuoran Yang (CoRR, 2025)