Publications & Preprints
You can also find my articles on my Google Scholar profile.
Journal Papers
- Sample Complexity of Variance-reduced Distributionally Robust Q-learning
- Shengbo Wang, Nian Si, Jose Blanchet, Zhengyuan Zhou.
- Accepted by Journal of Machine Learning Research.
Conference Papers
- An Efficient High-dimensional Gradient Estimator for Stochastic Differential Equations
- Shengbo Wang, Jose Blanchet, Peter Glynn.
- Accepted by Neural Information Processing Systems (NeurIPS) 2024.
- Optimal Sample Complexity for Average Reward Markov Decision Processes
- Shengbo Wang, Jose Blanchet, Peter Glynn.
- International Conference on Learning Representations (ICLR) 2024.
- A Finite Sample Complexity Bound for Distributionally Robust Q-learning
- Shengbo Wang, Nian Si, Jose Blanchet, Zhengyuan Zhou.
- Artificial Intelligence and Statistics Conference (AISTATS) 2023.
Preprints
- Statistical Learning of Distributionally Robust Stochastic Control in Continuous State Spaces
- Shengbo Wang, Nian Si, Jose Blanchet, Zhengyuan Zhou.
- Submitted.
- On the Foundation of Distributionally Robust Reinforcement Learning
- Shengbo Wang, Nian Si, Jose Blanchet, Zhengyuan Zhou.
- Under revision.
- Optimal Sample Complexity of Reinforcement Learning for Mixing Discounted Markov Decision Processes
- Shengbo Wang, Jose Blanchet, Peter Glynn.
- Submitted.
- Exact Exponential Tail Asymptotics of Markov Chain Additive Functionals Stopped at a Hitting Time
- Shengbo Wang, Jose Blanchet, Peter Glynn.
- Working Paper.