I am a Ph.D. candidate in the Department of Operations Research and Financial Engineering at Princeton University advised by Professor Jianqing Fan and Professor Han Liu. Prior to attending Princeton, I obtained a Bachelor of Mathematics degree from Tsinghua University.

My research interests lie in the interface between machine learning, statistics and optimization. The primary goal of my research is to design efficient learning algorithms for large-scale decision making problems that arise in reinforcement learning and stochastic games, with both statistical and computational guarantees. In addition, I am also interested in the applications of reinforcement learning such as computer games and robotics.

Education

• Princeton University.   2015 - present
  Ph.D. Candidate in Operations Research and Financial Engineering

• Tsinghua University.   2011 - 2015
  B.S. in Mathematics

• École Normale Supérieure (Paris).   Spring 2015
  Exchange Student

• University of Wisconsin-Madison.   Spring 2014
  Exchange Student

Journal Publications and Submissions

*: equal contribution or alphabetic ordering.

A Theoretical Analysis of Deep Q-Learning Jianqing Fan*, Zhaoran Wang*, Yuchen Xie* Zhuoran Yang* Submitted to Annals of Statistics, 2020   [arXiv]

High-dimensional Varying Index Coefficient Models via Stein’s Identity Sen Na, Zhuoran Yang, Zhaoran Wang, Mladen Kolar Journal of Machine Learning Research, 2019   [arXiv]

Misspecified Nonconvex Statistical Optimization for Phase Retrieval Zhuoran Yang*, Lin F. Yang*, Ethan X. Fang, Tuo Zhao, Zhaoran Wang, Matey Neykov Mathematical Programming, 2019   [arXiv]

On Semiparametric Exponential Family Graphical Models Zhuoran Yang, Yang Ning, Han Liu Journal of Machine Learning Research, 19(57):1−59, 2018   [Link]

Curse of Heterogeneity: Computational Barriers in Sparse Mixture Models and Phase Retrieval Jianqing Fan*, Han Liu*, Zhaoran Wang*, Zhuoran Yang* Submitted to Annals of Statistics, 2018   [arXiv]

Tensor Methods for Additive Index Models under Discordance and Heterogeneity Krishnakumar Balasubramanian*, Jianqing Fan*, Zhuoran Yang* Submitted to Annals of Statistics, 2018   [arXiv]

Provably Efficient Reinforcement Learning with Linear Function Approximation Chi Jin, Zhuoran Yang, Zhaoran Wang, Michael I. Jordan Submitted, 2019   [arXiv]

Robust One-Bit Recovery via ReLU Generative Networks: Improved Statistical Rates and Global Landscape Analysis Shuang Qiu*, Xiaohan Wei*, Zhuoran Yang Submitted, 2019   [arXiv]

Conference Publications

*: equal contribution or alphabetic ordering.

Provably Global Convergence of Actor-Critic: A Case for Linear Quadratic Regulator with Ergodic Cost Zhuoran Yang, Yongxin Chen, Mingyi Hong, Zhaoran Wang Advances in Neural Information Processing Systems (NeurIPS), 2019   [arXiv]

Neural Proximal Policy Optimization Attains Optimal Policy Boyi Liu, Qi Cai, Zhuoran Yang, Zhaoran Wang Advances in Neural Information Processing Systems (NeurIPS), 2019   [arXiv]

Neural Temporal-Difference Learning Converges to Global Optima Qi Cai, Zhuoran Yang, Jason D. Lee, Zhaoran Wang Advances in Neural Information Processing Systems (NeurIPS), 2019   [arXiv]

Policy Optimization Provably Converges to Nash Equilibria in Zero-Sum Linear Quadratic Games Kaiqing Zhang, Zhuoran Yang, Tamer Başar Advances in Neural Information Processing Systems (NeurIPS), 2019   [arXiv]

Statistical-Computational Tradeoff in Single Index Models Lingxiao Wang, Zhuoran Yang, Zhaoran Wang Advances in Neural Information Processing Systems (NeurIPS), 2019

Variance Reduced Policy Evaluation with Smooth Function Approximation Hoi-To Wai, Mingyi Hong, Zhuoran Yang, Zhaoran Wang, Kexin Tang Advances in Neural Information Processing Systems (NeurIPS), 2019

Convergent Policy Optimization for Safe Reinforcement Learning Ming Yu, Zhuoran Yang, Mladen Kolar, Zhaoran Wang Advances in Neural Information Processing Systems (NeurIPS), 2019

On the statistical rate of nonlinear recovery in generative models with heavy-tailed data Xiaohan Wei, Zhuoran Yang, Zhaoran Wang International Conference on Machine Learning (ICML), 2019   [Link]

A Finite Sample Analysis of the Actor-Critic Algorithm Kaiqing Zhang, Zhuoran Yang, Tamer Başar IEEE Conference on Decision and Control (CDC), 2018   [Link]

Networked Multi-Agent Reinforcement Learning in Continuous Spaces Kaiqing Zhang, Zhuoran Yang, Tamer Başar IEEE Conference on Decision and Control (CDC), 2018   [Link]

Multi-agent reinforcement learning via double averaging primal-dual optimization Hoi-To Wai, Zhuoran Yang, Zhaoran Wang, Mingyi Hong Advances in Neural Information Processing Systems (NeurIPS), 2018   [arXiv]

Provable Gaussian Embedding with One Observation Ming Yu, Zhuoran Yang, Tuo Zhao, Mladen Kolar, Zhaoran Wang Advances in Neural Information Processing Systems (NeurIPS), 2018   [arXiv]

Contrastive Learning from Pairwise Measurements Yi Chen, Zhuoran Yang, Yuchen Xie, Zhaoran Wang Advances in Neural Information Processing Systems (NeurIPS), 2018   [Link]

Fully Decentralized Multi-Agent Reinforcement Learning with Networked Agents Kaiqing Zhang, Zhuoran Yang, Han Liu, Tong Zhang, Tamer Başar International Conference on Machine Learning (ICML), 2018   [arXiv]

The Edge Density Barrier: Computational-Statistical Tradeoffs in Combinatorial Inference Hao Lu, Yuan Cao, Zhuoran Yang, Junwei Lu, Han Liu, Zhaoran Wang International Conference on Machine Learning (ICML), 2018   [Link]

Nonlinear Structured Signal Estimation in High Dimensions via Iterative Hard Thresholding. Kaiqing Zhang, Zhuoran Yang, Zhaoran Wang International Conference on Artificial Intelligence and Statistics (AISTATS), 2018   [Link]

Estimating High-dimensional Non-Gaussian Multiple Index Models via Stein’s Lemma Zhuoran Yang, Krishna Balasubramanian, Zhaoran Wang, Han Liu Advances in Neural Information Processing Systems (NeurIPS), 2017   [Link]   [arXiv, Long Version]

High-dimensional Non-Gaussian Single Index Models via Thresholded Score Function Estimation Zhuoran Yang, Krishnakumar Balasubramanian, Han Liu International Conference on Machine Learning (ICML), 2017   [Link]

More Supervision, Less Computation: Statistical-Computational Tradeoffs in Weakly Supervised Learning Xinyang Yi*, Zhaoran Wang*, Zhuoran Yang*, Constantine Caramanis, Han Liu Advances in Neural Information Processing Systems (NeurIPS), 2016   [Link]

Sparse Nonlinear Regression: Parameter Estimation and Asymptotic Inference Zhuoran Yang, Zhaoran Wang, Han Liu, Yonina C. Eldar, Tong Zhang International Conference on Machine Learning (ICML), 2016   [arXiv]

Human Memory Search as Initial-Visit Emitting Random Walk Kwang-Sung Jun, Xiaojin (Jerry) Zhu, Timothy T. Rogers, Zhuoran Yang, Ming Yuan Advances in Neural Information Processing Systems (NeurIPS), 2015   [Link]

Preprints

*: equal contribution or alphabetic ordering.

Neural Policy Gradient Methods: Global Optimality and Rates of Convergence Lingxiao Wang*, Qi Cai*, Zhuoran Yang, Zhaoran Wang [arXiv]

A Multi-Agent Off-Policy Actor-Critic Algorithm for Distributed Reinforcement Learning Wesley Suttle, Zhuoran Yang, Kaiqing Zhang, Zhaoran Wang, Tamer Başar , Ji Liu [arXiv]

Fast Multi-Agent Temporal-Difference Learning via Homotopy Stochastic Primal-Dual Optimization Dongsheng Ding, Xiaohan Wei, Zhuoran Yang, Zhaoran Wang, Mihailo R. Jovanović [arXiv]

Finite-Sample Analyses for Fully Decentralized Multi-Agent Reinforcement Learning Kaiqing Zhang, Zhuoran Yang, Han Liu, Tong Zhang, Tamer Başar [arXiv]

Parametrized Deep Q-Networks Learning: Reinforcement Learning with Discrete-Continuous Hybrid Action Space Jiechao Xiong, Qing Wang, Zhuoran Yang, Peng Sun, Lei Han, Yang Zheng, Haobo Fu, Tong Zhang, Ji Liu, Han Liu [arXiv]