ML Anthology

Yang, Zhuoran

143 publications

ICML 2025 An Instrumental Value for Data Production and Its Application to Data Pricing Rui Ai, Boxiang Lyu, Zhaoran Wang, Zhuoran Yang, Haifeng Xu
ICML 2025 BanditSpec: Adaptive Speculative Decoding via Bandit Algorithms Yunlong Hou, Fengzhuo Zhang, Cunxiao Du, Xuan Zhang, Jiachun Pan, Tianyu Pang, Chao Du, Vincent Tan, Zhuoran Yang
ICLR 2025 Can Neural Networks Achieve Optimal Computational-Statistical Tradeoff? an Analysis on Single-Index Model Siyu Chen, Beining Wu, Miao Lu, Zhuoran Yang, Tianhao Wang
ICML 2025 Decoding Rewards in Competitive Games: Inverse Game Theory with Entropy Regularization Junyi Liao, Zihan Zhu, Ethan X Fang, Zhuoran Yang, Vahid Tarokh
ICML 2025 In-Context Linear Regression Demystified: Training Dynamics and Mechanistic Interpretability of Multi-Head SoftMax Attention Jianliang He, Xintian Pan, Siyu Chen, Zhuoran Yang
ICML 2025 In-Context Reinforcement Learning from Suboptimal Historical Data Juncheng Dong, Moyang Guo, Ethan X Fang, Zhuoran Yang, Vahid Tarokh
ICCV 2025 InstaDrive: Instance-Aware Driving World Models for Realistic and Consistent Video Generation Zhuoran Yang, Xi Guo, Chenjing Ding, Chiyu Wang, Wei Wu, Yanyong Zhang
JMLR 2025 Principled Penalty-Based Methods for Bilevel Reinforcement Learning and RLHF Han Shen, Zhuoran Yang, Tianyi Chen
CoRL 2025 Reflective Planning: Vision-Language Models for Multi-Stage Long-Horizon Robotic Manipulation Yunhai Feng, Jiaming Han, Zhuoran Yang, Xiangyu Yue, Sergey Levine, Jianlan Luo
ICML 2025 The Sample Complexity of Online Strategic Decision Making with Information Asymmetry and Knowledge Transportability Jiachen Hu, Rui Ai, Han Zhong, Xiaoyu Chen, Liwei Wang, Zhaoran Wang, Zhuoran Yang
AISTATS 2025 What and How Does In-Context Learning Learn? Bayesian Model Averaging, Parameterization, and Generalization Yufeng Zhang, Fengzhuo Zhang, Zhuoran Yang, Zhaoran Wang
ICML 2024 A General Framework for Sequential Decision-Making Under Adaptivity Constraints Nuoya Xiong, Zhaoran Wang, Zhuoran Yang
NeurIPSW 2024 Can Neural Networks Achieve Optimal Computational-Statistical Tradeoff? an Analysis on Single-Index Model Siyu Chen, Beining Wu, Miao Lu, Zhuoran Yang, Tianhao Wang
ICLRW 2024 Empowering Autonomous Driving with Large Language Models: A Safety Perspective Yixuan Wang, Ruochen Jiao, Simon Sinong Zhan, Chengtian Lang, Chao Huang, Zhaoran Wang, Zhuoran Yang, Qi Zhu
ICML 2024 From Words to Actions: Unveiling the Theoretical Underpinnings of LLM-Driven Autonomous Systems Jianliang He, Siyu Chen, Fengzhuo Zhang, Zhuoran Yang
ICML 2024 How Does Goal Relabeling Improve Sample Efficiency? Sirui Zheng, Chenjia Bai, Zhuoran Yang, Zhaoran Wang
ICMLW 2024 In-Context Reinforcement Learning Without Optimal Action Labels Juncheng Dong, Moyang Guo, Ethan X Fang, Zhuoran Yang, Vahid Tarokh
JMLR 2024 Instrumental Variable Value Iteration for Causal Offline Reinforcement Learning Luofeng Liao, Zuyue Fu, Zhuoran Yang, Yixin Wang, Dingli Ma, Mladen Kolar, Zhaoran Wang
JMLR 2024 Learning Dynamic Mechanisms in Unknown Environments: A Reinforcement Learning Approach Shuang Qiu, Boxiang Lyu, Qinglin Meng, Zhaoran Wang, Zhuoran Yang, Michael I. Jordan
JMLR 2024 Learning Regularized Graphon Mean-Field Games with Unknown Graphons Fengzhuo Zhang, Vincent Y. F. Tan, Zhaoran Wang, Zhuoran Yang
ICMLW 2024 Learning Task Representations from In-Context Learning Baturay Saglam, Zhuoran Yang, Dionysis Kalogerias, Amin Karbasi
ICML 2024 Mean Field Langevin Actor-Critic: Faster Convergence and Global Optimality Beyond Lazy Learning Kakei Yamamoto, Kazusato Oko, Zhuoran Yang, Taiji Suzuki
NeurIPS 2024 On the Role of Information Structure in Reinforcement Learning for Partially-Observable Sequential Teams and Games Awni Altabaa, Zhuoran Yang
ICML 2024 Principled Penalty-Based Methods for Bilevel Reinforcement Learning and RLHF Han Shen, Zhuoran Yang, Tianyi Chen
ICMLW 2024 STRIDE: A Tool-Assisted LLM Agent Framework for Strategic and Interactive Decision-Making Chuanhao Li, Runhan Yang, Tiankai Li, Milad Bafarassat, Kourosh Sharifi, Dirk Bergemann, Zhuoran Yang
ICMLW 2024 STRIDE: A Tool-Assisted LLM Agent Framework for Strategic and Interactive Decision-Making Chuanhao Li, Runhan Yang, Tiankai Li, Milad Bafarassat, Kourosh Sharifi, Dirk Bergemann, Zhuoran Yang
ICLR 2024 Sample-Efficient Learning of Infinite-Horizon Average-Reward MDPs with General Function Approximation Jianliang He, Han Zhong, Zhuoran Yang
ICLR 2024 Sample-Efficient Multi-Agent RL: An Optimization Perspective Nuoya Xiong, Zhihan Liu, Zhaoran Wang, Zhuoran Yang
ICLR 2024 Symmetric Mean-Field Langevin Dynamics for Distributional Minimax Problems Juno Kim, Kakei Yamamoto, Kazusato Oko, Zhuoran Yang, Taiji Suzuki
ICML 2024 Theory of Consistency Diffusion Models: Distribution Estimation Meets Fast Sampling Zehao Dou, Minshuo Chen, Mengdi Wang, Zhuoran Yang
NeurIPS 2024 Unveiling Induction Heads: Provable Training Dynamics and Feature Learning in Transformers Siyu Chen, Heejune Sheen, Tianhao Wang, Zhuoran Yang
ICMLW 2024 Unveiling Induction Heads: Provable Training Dynamics and Feature Learning in Transformers Siyu Chen, Heejune Sheen, Tianhao Wang, Zhuoran Yang
JMLR 2023 Can Reinforcement Learning Find Stackelberg-Nash Equilibria in General-Sum Markov Games with Myopically Rational Followers? Han Zhong, Zhuoran Yang, Zhaoran Wang, Michael I. Jordan
ICLR 2023 Can We Find Nash Equilibria at a Linear Rate in Markov Games? Zhuoqing Song, Jason D. Lee, Zhuoran Yang
ICLR 2023 Decentralized Optimistic Hyperpolicy Mirror Descent: Provably No-Regret Learning in Markov Games Wenhao Zhan, Jason D. Lee, Zhuoran Yang
NeurIPS 2023 Diffusion Model Is an Effective Planner and Data Synthesizer for Multi-Task Reinforcement Learning Haoran He, Chenjia Bai, Kang Xu, Zhuoran Yang, Weinan Zhang, Dong Wang, Bin Zhao, Xuelong Li
JMLR 2023 Double Duality: Variational Primal-Dual Policy Optimization for Constrained Reinforcement Learning Zihao Li, Boyi Liu, Zhuoran Yang, Zhaoran Wang, Mengdi Wang
ICML 2023 Enforcing Hard Constraints with Soft Barriers: Safe Reinforcement Learning in Unknown Stochastic Environments Yixuan Wang, Simon Sinong Zhan, Ruochen Jiao, Zhilu Wang, Wanxin Jin, Zhuoran Yang, Zhaoran Wang, Chao Huang, Qi Zhu
AISTATS 2023 Finding Regularized Competitive Equilibria of Heterogeneous Agent Macroeconomic Models via Reinforcement Learning Ruitu Xu, Yifei Min, Tianhao Wang, Michael I. Jordan, Zhaoran Wang, Zhuoran Yang
NeurIPSW 2023 In-Context Multi-Armed Bandits via Supervised Pretraining Fred Weiying Zhang, Jiaxin Ye, Zhuoran Yang
NeurIPS 2023 Learning Regularized Monotone Graphon Mean-Field Games Fengzhuo Zhang, Vincent Tan, Zhaoran Wang, Zhuoran Yang
ICML 2023 Learning to Incentivize Information Acquisition: Proper Scoring Rules Meet Principal-Agent Model Siyu Chen, Jibang Wu, Yifan Wu, Zhuoran Yang
ICML 2023 Local Optimization Achieves Global Optimality in Multi-Agent Reinforcement Learning Yulai Zhao, Zhuoran Yang, Zhaoran Wang, Jason D. Lee
NeurIPS 2023 Maximize to Explore: One Objective Function Fusing Estimation, Planning, and Exploration Zhihan Liu, Miao Lu, Wei Xiong, Han Zhong, Hao Hu, Shenao Zhang, Sirui Zheng, Zhuoran Yang, Zhaoran Wang
ICLR 2023 Offline RL with No OOD Actions: In-Sample Learning via Implicit Value Regularization Haoran Xu, Li Jiang, Jianxiong Li, Zhuoran Yang, Zhaoran Wang, Victor Wai Kin Chan, Xianyuan Zhan
NeurIPS 2023 Online Performative Gradient Descent for Learning Nash Equilibria in Decision-Dependent Games Zihan Zhu, Ethan Fang, Zhuoran Yang
ICLR 2023 Optimistic Exploration with Learned Features Provably Solves Markov Decision Processes with Neural Dynamics Sirui Zheng, Lingxiao Wang, Shuang Qiu, Zuyue Fu, Zhuoran Yang, Csaba Szepesvari, Zhaoran Wang
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, Zhuoran Yang
NeurIPS 2023 Posterior Sampling for Competitive RL: Function Approximation and Partial Observation Shuang Qiu, Ziyu Dai, Han Zhong, Zhaoran Wang, Zhuoran Yang, Tong Zhang
L4DC 2023 Provably Efficient Generalized Lagrangian Policy Optimization for Safe Multi-Agent Reinforcement Learning Dongsheng Ding, Xiaohan Wei, Zhuoran Yang, Zhaoran Wang, Mihailo Jovanovic
ICML 2023 Provably Efficient Representation Learning with Tractable Planning in Low-Rank POMDP Jiacheng Guo, Zihao Li, Huazheng Wang, Mengdi Wang, Zhuoran Yang, Xuezhou Zhang
ICMLW 2023 Reinforcement Learning with Human Feedback: Learning Dynamic Choices via Pessimism Zihao Li, Zhuoran Yang, Mengdi Wang
ICLR 2023 Represent to Control Partially Observed Systems: Representation Learning with Provable Sample Efficiency Lingxiao Wang, Qi Cai, Zhuoran Yang, Zhaoran Wang
NeurIPSW 2023 Symmetric Mean-Field Langevin Dynamics for Distributional Minimax Problems Juno Kim, Kakei Yamamoto, Kazusato Oko, Zhuoran Yang, Taiji Suzuki
AISTATS 2022 Gap-Dependent Bounds for Two-Player Markov Games Zehao Dou, Zhuoran Yang, Zhaoran Wang, Simon Du
NeurIPS 2022 A Unifying Framework of Off-Policy General Value Function Evaluation Tengyu Xu, Zhuoran Yang, Zhaoran Wang, Yingbin Liang
ICML 2022 Adaptive Model Design for Markov Decision Process Siyu Chen, Donglin Yang, Jiayang Li, Senmiao Wang, Zhuoran Yang, Zhaoran Wang
ICLRW 2022 Can Reinforcement Learning Efficiently Find Stackelberg-Nash Equilibria in General-Sum Markov Games with Myopic Followers？ Han Zhong, Zhuoran Yang, Zhaoran Wang, Michael Jordan
ICML 2022 Contrastive UCB: Provably Efficient Contrastive Self-Supervised Learning in Online Reinforcement Learning Shuang Qiu, Lingxiao Wang, Chenjia Bai, Zhuoran Yang, Zhaoran Wang
NeurIPS 2022 Exponential Family Model-Based Reinforcement Learning via Score Matching Gene Li, Junbo Li, Anmol Kabra, Nati Srebro, Zhaoran Wang, Zhuoran Yang
ICML 2022 Human-in-the-Loop: Provably Efficient Preference-Based Reinforcement Learning with General Function Approximation Xiaoyu Chen, Han Zhong, Zhuoran Yang, Zhaoran Wang, Liwei Wang
NeurIPS 2022 Inducing Equilibria via Incentives: Simultaneous Design-and-Play Ensures Global Convergence Boyi Liu, Jiayang Li, Zhuoran Yang, Hoi-To Wai, Mingyi Hong, Yu Nie, Zhaoran Wang
NeurIPS 2022 Learn to Match with No Regret: Reinforcement Learning in Markov Matching Markets Yifei Min, Tianhao Wang, Ruitu Xu, Zhaoran Wang, Michael I. Jordan, Zhuoran Yang
ICML 2022 Learning from Demonstration: Provably Efficient Adversarial Policy Imitation with Linear Function Approximation Zhihan Liu, Yufeng Zhang, Zuyue Fu, Zhuoran Yang, Zhaoran Wang
ICML 2022 Pessimism Meets VCG: Learning Dynamic Mechanism Design via Offline Reinforcement Learning Boxiang Lyu, Zhaoran Wang, Mladen Kolar, Zhuoran Yang
ICLR 2022 Pessimistic Bootstrapping for Uncertainty-Driven Offline Reinforcement Learning Chenjia Bai, Lingxiao Wang, Zhuoran Yang, Zhi-Hong Deng, Animesh Garg, Peng Liu, Zhaoran Wang
ICML 2022 Pessimistic Minimax Value Iteration: Provably Efficient Equilibrium Learning from Offline Datasets Han Zhong, Wei Xiong, Jiyuan Tan, Liwei Wang, Tong Zhang, Zhaoran Wang, Zhuoran Yang
ICLRW 2022 Pessimistic Minimax Value Iteration: Provably Efficient Equilibrium Learning from Offline Datasets Han Zhong, Wei Xiong, Jiyuan Tan, Liwei Wang, Tong Zhang, Zhaoran Wang, Zhuoran Yang
ICML 2022 Provably Efficient Offline Reinforcement Learning for Partially Observable Markov Decision Processes Hongyi Guo, Qi Cai, Yufeng Zhang, Zhuoran Yang, Zhaoran Wang
ICLR 2022 Reinforcement Learning Under a Multi-Agent Predictive State Representation Model: Method and Theory Zhi Zhang, Zhuoran Yang, Han Liu, Pratap Tokekar, Furong Huang
ICML 2022 Reinforcement Learning from Partial Observation: Linear Function Approximation with Provable Sample Efficiency Qi Cai, Zhuoran Yang, Zhaoran Wang
NeurIPS 2022 Reinforcement Learning with Logarithmic Regret and Policy Switches Grigoris Velegkas, Zhuoran Yang, Amin Karbasi
NeurIPS 2022 Relational Reasoning via Set Transformers: Provable Efficiency and Applications to MARL Fengzhuo Zhang, Boyi Liu, Kaixin Wang, Vincent Tan, Zhuoran Yang, Zhaoran Wang
NeurIPSW 2022 Sparse Q-Learning: Offline Reinforcement Learning with Implicit Value Regularization Haoran Xu, Li Jiang, Jianxiong Li, Zhuoran Yang, Zhaoran Wang, Xianyuan Zhan
ICLR 2022 Towards General Function Approximation in Zero-Sum Markov Games Baihe Huang, Jason D. Lee, Zhaoran Wang, Zhuoran Yang
ICML 2022 Welfare Maximization in Competitive Equilibrium: Reinforcement Learning for Markov Exchange Economy Zhihan Liu, Miao Lu, Zhaoran Wang, Michael Jordan, Zhuoran Yang
AISTATS 2021 Provably Efficient Safe Exploration via Primal-Dual Policy Optimization Dongsheng Ding, Xiaohan Wei, Zhuoran Yang, Zhaoran Wang, Mihailo Jovanovic
AISTATS 2021 Provably Efficient Actor-Critic for Risk-Sensitive and Robust Adversarial RL: A Linear-Quadratic Case Yufeng Zhang, Zhuoran Yang, Zhaoran Wang
AISTATS 2021 Sample Elicitation Jiaheng Wei, Zuyue Fu, Yang Liu, Xingyu Li, Zhuoran Yang, Zhaoran Wang
NeurIPS 2021 A Near-Optimal Algorithm for Stochastic Bilevel Optimization via Double-Momentum Prashant Khanduri, Siliang Zeng, Mingyi Hong, Hoi-To Wai, Zhaoran Wang, Zhuoran Yang
NeurIPS 2021 BooVI: Provably Efficient Bootstrapped Value Iteration Boyi Liu, Qi Cai, Zhuoran Yang, Zhaoran Wang
ICML 2021 Decentralized Single-Timescale Actor-Critic on Zero-Sum Two-Player Stochastic Games Hongyi Guo, Zuyue Fu, Zhuoran Yang, Zhaoran Wang
ICML 2021 Doubly Robust Off-Policy Actor-Critic: Convergence and Optimality Tengyu Xu, Zhuoran Yang, Zhaoran Wang, Yingbin Liang
NeurIPSW 2021 ElegantRL-Podracer: Scalable and Elastic Library for Cloud-Native Deep Reinforcement Learning Xiao-Yang Liu, Zechu Li, Zhuoran Yang, Jiahao Zheng, Zhaoran Wang, Anwar Walid, Jian Guo, Michael Jordan
NeurIPS 2021 Exponential Bellman Equation and Improved Regret Bounds for Risk-Sensitive Reinforcement Learning Yingjie Fei, Zhuoran Yang, Yudong Chen, Zhaoran Wang
NeurIPSW 2021 Exponential Family Model-Based Reinforcement Learning via Score Matching Gene Li, Junbo Li, Nathan Srebro, Zhaoran Wang, 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
ICML 2021 Infinite-Dimensional Optimization for Zero-Sum Games via Variational Transport Lewis Liu, Yufeng Zhang, Zhuoran Yang, Reza Babanezhad, Zhaoran Wang
ICML 2021 Is Pessimism Provably Efficient for Offline RL? Ying Jin, Zhuoran Yang, Zhaoran Wang
ICML 2021 Learning While Playing in Mean-Field Games: Convergence and Optimality Qiaomin Xie, Zhuoran Yang, Zhaoran Wang, Andreea Minca
NeurIPS 2021 Offline Constrained Multi-Objective Reinforcement Learning via Pessimistic Dual Value Iteration Runzhe Wu, Yufeng Zhang, Zhuoran Yang, Zhaoran Wang
ICML 2021 On Reward-Free RL with Kernel and Neural Function Approximations: Single-Agent MDP and Markov Game Shuang Qiu, Jieping Ye, Zhaoran Wang, Zhuoran Yang
NeurIPS 2021 Pessimism Meets Invariance: Provably Efficient Offline Mean-Field Multi-Agent RL Minshuo Chen, Yan Li, Ethan Wang, Zhuoran Yang, Zhaoran Wang, Tuo Zhao
NeurIPS 2021 Provably Efficient Causal Reinforcement Learning with Confounded Observational Data Lingxiao Wang, Zhuoran Yang, Zhaoran Wang
ICML 2021 Provably Efficient Fictitious Play Policy Optimization for Zero-Sum Markov Games with Structured Transitions Shuang Qiu, Xiaohan Wei, Jieping Ye, Zhaoran Wang, Zhuoran Yang
L4DC 2021 Provably Sample Efficient Reinforcement Learning in Competitive Linear Quadratic Systems Jingwei Zhang, Zhuoran Yang, Zhengyuan Zhou, Zhaoran Wang
ICML 2021 Randomized Exploration in Reinforcement Learning with General Value Function Approximation Haque Ishfaq, Qiwen Cui, Viet Nguyen, Alex Ayoub, Zhuoran Yang, Zhaoran Wang, Doina Precup, Lin Yang
ICML 2021 Reinforcement Learning for Cost-Aware Markov Decision Processes Wesley Suttle, Kaiqing Zhang, Zhuoran Yang, Ji Liu, David Kraemer
ICML 2021 Risk-Sensitive Reinforcement Learning with Function Approximation: A Debiasing Approach Yingjie Fei, Zhuoran Yang, Zhaoran Wang
ICLR 2021 Single-Timescale Actor-Critic Provably Finds Globally Optimal Policy Zuyue Fu, Zhuoran Yang, Zhaoran Wang
NeurIPS 2021 Wasserstein Flow Meets Replicator Dynamics: A Mean-Field Analysis of Representation Learning in Actor-Critic Yufeng Zhang, Siyu Chen, Zhuoran Yang, Michael I. Jordan, Zhaoran Wang
L4DC 2020 A Theoretical Analysis of Deep Q-Learning Jianqing Fan, Zhaoran Wang, Yuchen Xie, Zhuoran Yang
ICLR 2020 Actor-Critic Provably Finds Nash Equilibria of Linear-Quadratic Mean-Field Games Zuyue Fu, Zhuoran Yang, Yongxin Chen, Zhaoran Wang
ICML 2020 Breaking the Curse of Many Agents: Provable Mean Embedding Q-Iteration for Mean-Field Reinforcement Learning Lingxiao Wang, Zhuoran Yang, Zhaoran Wang
NeurIPS 2020 Can Temporal-Difference and Q-Learning Learn Representation? a Mean-Field Theory Yufeng Zhang, Qi Cai, Zhuoran Yang, Yongxin Chen, Zhaoran Wang
NeurIPS 2020 Dynamic Regret of Policy Optimization in Non-Stationary Environments Yingjie Fei, Zhuoran Yang, Zhaoran Wang, Qiaomin Xie
ICML 2020 Generative Adversarial Imitation Learning with Neural Network Parameterization: Global Optimality and Convergence Rate Yufeng Zhang, Qi Cai, Zhuoran Yang, Zhaoran Wang
COLT 2020 Learning Zero-Sum Simultaneous-Move Markov Games Using Function Approximation and Correlated Equilibrium Qiaomin Xie, Yudong Chen, Zhaoran Wang, Zhuoran Yang
ICLR 2020 Neural Policy Gradient Methods: Global Optimality and Rates of Convergence Lingxiao Wang, Qi Cai, Zhuoran Yang, Zhaoran Wang
ICLR 2020 On Computation and Generalization of Generative Adversarial Imitation Learning Minshuo Chen, Yizhou Wang, Tianyi Liu, Zhuoran Yang, Xingguo Li, Zhaoran Wang, Tuo Zhao
ICML 2020 On the Global Optimality of Model-Agnostic Meta-Learning Lingxiao Wang, Qi Cai, Zhuoran Yang, Zhaoran Wang
NeurIPS 2020 Pontryagin Differentiable Programming: An End-to-End Learning and Control Framework Wanxin Jin, Zhaoran Wang, Zhuoran Yang, Shaoshuai Mou
ICML 2020 Provably Efficient Exploration in Policy Optimization Qi Cai, Zhuoran Yang, Chi Jin, Zhaoran Wang
NeurIPS 2020 Provably Efficient Neural Estimation of Structural Equation Models: An Adversarial Approach Luofeng Liao, You-Lin Chen, Zhuoran Yang, Bo Dai, Mladen Kolar, Zhaoran Wang
NeurIPS 2020 Provably Efficient Neural GTD for Off-Policy Learning Hoi-To Wai, Zhuoran Yang, Zhaoran Wang, Mingyi Hong
NeurIPS 2020 Provably Efficient Reinforcement Learning with Kernel and Neural Function Approximations Zhuoran Yang, Chi Jin, Zhaoran Wang, Mengdi Wang, Michael I. Jordan
COLT 2020 Provably Efficient Reinforcement Learning with Linear Function Approximation Chi Jin, Zhuoran Yang, Zhaoran Wang, Michael I Jordan
NeurIPS 2020 Risk-Sensitive Reinforcement Learning: Near-Optimal Risk-Sample Tradeoff in Regret Yingjie Fei, Zhuoran Yang, Yudong Chen, Zhaoran Wang, Qiaomin Xie
ICML 2020 Robust One-Bit Recovery via ReLU Generative Networks: Near-Optimal Statistical Rate and Global Landscape Analysis Shuang Qiu, Xiaohan Wei, Zhuoran Yang
ICML 2020 Semiparametric Nonlinear Bipartite Graph Representation Learning with Provable Guarantees Sen Na, Yuwei Luo, Zhuoran Yang, Zhaoran Wang, Mladen Kolar
NeurIPS 2020 Upper Confidence Primal-Dual Reinforcement Learning for CMDP with Adversarial Loss Shuang Qiu, Xiaohan Wei, Zhuoran Yang, Jieping Ye, Zhaoran Wang
NeurIPS 2019 Convergent Policy Optimization for Safe Reinforcement Learning Ming Yu, Zhuoran Yang, Mladen Kolar, Zhaoran Wang
JMLR 2019 High-Dimensional Varying Index Coefficient Models via Stein's Identity Sen Na, Zhuoran Yang, Zhaoran Wang, Mladen Kolar
NeurIPS 2019 Neural Temporal-Difference Learning Converges to Global Optima Qi Cai, Zhuoran Yang, Jason Lee, Zhaoran Wang
NeurIPS 2019 Neural Trust Region/Proximal Policy Optimization Attains Globally Optimal Policy Boyi Liu, Qi Cai, Zhuoran Yang, Zhaoran Wang
ICML 2019 On the Statistical Rate of Nonlinear Recovery in Generative Models with Heavy-Tailed Data Xiaohan Wei, Zhuoran Yang, Zhaoran Wang
NeurIPS 2019 Policy Optimization Provably Converges to Nash Equilibria in Zero-Sum Linear Quadratic Games Kaiqing Zhang, Zhuoran Yang, Tamer Basar
NeurIPS 2019 Provably Global Convergence of Actor-Critic: A Case for Linear Quadratic Regulator with Ergodic Cost Zhuoran Yang, Yongxin Chen, Mingyi Hong, Zhaoran Wang
NeurIPSW 2019 Robust One-Bit Recovery via ReLU Generative Networks: Improved Statistical Rate and Global Landscape Analysis Shuang Qiu, Xiaohan Wei, Zhuoran Yang
NeurIPS 2019 Statistical-Computational Tradeoff in Single Index Models Lingxiao Wang, Zhuoran Yang, Zhaoran Wang
NeurIPS 2019 Variance Reduced Policy Evaluation with Smooth Function Approximation Hoi-To Wai, Mingyi Hong, Zhuoran Yang, Zhaoran Wang, Kexin Tang
NeurIPS 2018 Contrastive Learning from Pairwise Measurements Yi Chen, Zhuoran Yang, Yuchen Xie, Zhaoran Wang
ICML 2018 Fully Decentralized Multi-Agent Reinforcement Learning with Networked Agents Kaiqing Zhang, Zhuoran Yang, Han Liu, Tong Zhang, Tamer Basar
NeurIPS 2018 Multi-Agent Reinforcement Learning via Double Averaging Primal-Dual Optimization Hoi-To Wai, Zhuoran Yang, Zhaoran Wang, Mingyi Hong
AISTATS 2018 Nonlinear Structured Signal Estimation in High Dimensions via Iterative Hard Thresholding Kaiqing Zhang, Zhuoran Yang, Zhaoran Wang
JMLR 2018 On Semiparametric Exponential Family Graphical Models Zhuoran Yang, Yang Ning, Han Liu
NeurIPS 2018 Provable Gaussian Embedding with One Observation Ming Yu, Zhuoran Yang, Tuo Zhao, Mladen Kolar, Zhaoran Wang
ICML 2018 The Edge Density Barrier: Computational-Statistical Tradeoffs in Combinatorial Inference Hao Lu, Yuan Cao, Zhuoran Yang, Junwei Lu, Han Liu, Zhaoran Wang
NeurIPS 2017 Estimating High-Dimensional Non-Gaussian Multiple Index Models via Stein’s Lemma Zhuoran Yang, Krishnakumar Balasubramanian, Zhaoran Wang, Han Liu
ICML 2017 High-Dimensional Non-Gaussian Single Index Models via Thresholded Score Function Estimation Zhuoran Yang, Krishnakumar Balasubramanian, Han Liu
NeurIPS 2016 More Supervision, Less Computation: Statistical-Computational Tradeoffs in Weakly Supervised Learning Xinyang Yi, Zhaoran Wang, Zhuoran Yang, Constantine Caramanis, Han Liu
ICML 2016 Sparse Nonlinear Regression: Parameter Estimation Under Nonconvexity Zhuoran Yang, Zhaoran Wang, Han Liu, Yonina Eldar, Tong Zhang
NeurIPS 2015 Human Memory Search as Initial-Visit Emitting Random Walk Kwang-Sung Jun, Xiaojin Zhu, Timothy T. Rogers, Zhuoran Yang, Ming Yuan