- A Dual Accelerated Method for Online Stochastic Distributed Averaging: From Consensus to Decentralized Policy Evaluation, with Ashwin Pananjady and Justin Romberg, under review by IEEE Transactions on Automatic Control.
- Preliminary version was accepted by IEEE Conference on Decision and Control 2022.
- Finite Sample Analysis of Average-Reward TD Learning and Q-Learning, with Zhe Zhang and Siva Theja Maguluri, NeurIPS 2021 (acceptance rate 26%)[talk][code].
- Preliminary version was accepted by ICML 2021 Workshop on Reinforcement Learning Theory.
- DouZero: Mastering DouDizhu with Self-Play Deep Reinforcement Learning, with Daochen Zha, Jingru Xie, Wenye Ma, Xiangru Lian, Xia Hu and Ji Liu, ICML 2021 (acceptance rate 21.5%)[code][demo].
- Self-Diagnostic Mobile App: Common Bile Duct Stone Evaluation for Pediatric Patients, with Hongzhen Tian, Reuven Zev Cohen, Yajun Mei and A. Jay Freeman, The 2020 NASPGHAN Annual Conference.
- Finite-Sample Analysis of Nonlinear Stochastic Approximation with Applications in Reinforcement Learning, with Zaiwei Chen, Thinh T. Doan, Siva Theja Maguluri and John-Paul Clarke, Automatica [code].
- Preliminary version was accepted by NeurIPS 2019 Optimization Foundations for Reinforcement Learning Workshop.
- Automated Planning in Master Production Plans Based on Artificial Intelligence, Machine Learning and Optimization, with Huan Xu and Chelsea White and Sukun Park, Supported by Samsung Electronics Co., Ltd.
- Hierarchical Temporal Regularized Matrix Factorization for High-Dimensional Demand Forecasting with Missing Values, with Ming Li, Alibaba’s Internal Conference 2018.
- Automatic Event Detection in Basketball using HMM with Energy based Defensive Assignment, with Suraj Keshri, Min-hwan Oh and Garud Iyengar, The Journal of Quantitative Analysis in Sports 15(2), 141-153.
Sheng Zhang 