| 2024 | ICLR | Optimal Sample Complexity for Average Reward Markov Decision Processes. | Shengbo Wang, Jos H. Blanchet, Peter W. Glynn |
| 2024 | ICML | Stability Evaluation through Distributional Perturbation Analysis. | Jos H. Blanchet, Peng Cui, Jiajin Li, Jiashuo Liu |
| 2024 | ICML | Single-Trajectory Distributionally Robust Reinforcement Learning. | Zhipeng Liang, Xiaoteng Ma, Jos H. Blanchet, Jun Yang, Jiheng Zhang, Zhengyuan Zhou |
| 2024 | ICML | Orthogonal Bootstrap: Efficient Simulation of Input Uncertainty. | Kaizhao Liu, Jos H. Blanchet, Lexing Ying, Yiping Lu |
| 2023 | AISTATS | A Finite Sample Complexity Bound for Distributionally Robust Q-learning. | Shengbo Wang, Nian Si, Jos H. Blanchet, Zhengyuan Zhou |
| 2023 | ICLR | Minimax Optimal Kernel Operator Learning via Multilevel Training. | Jikai Jin, Yiping Lu, Jos H. Blanchet, Lexing Ying |
| 2022 | AISTATS | A Class of Geometric Structures in Transfer Learning: Minimax Bounds and Optimality. | Xuhui Zhang, Jos H. Blanchet, Soumyadip Ghosh, Mark S. Squillante |
| 2019 | WSC | Data-Driven Optimal Transport Cost Selection For Distributionally Robust Optimization. | Jos H. Blanchet, Yang Kang, Karthyek R. A. Murthy, Fan Zhang |