| 2025 | AISTATS | Spectral Representation for Causal Estimation with Hidden Confounders. | Haotian Sun, Antoine Moulin, Tongzheng Ren, Arthur Gretton, Bo Dai |
| 2024 | ICML | Improving Computational Complexity in Statistical Models with Local Curvature Information. | Pedram Akbarian, Tongzheng Ren, Jiacheng Zhuo, Sujay Sanghavi, Nhat Ho |
| 2024 | ICML | Provable Representation with Efficient Planning for Partially Observable Reinforcement Learning. | Hongming Zhang, Tongzheng Ren, Chenjun Xiao, Dale Schuurmans, Bo Dai |
| 2023 | ICLR | Hierarchical Sliced Wasserstein Distance. | Khai Nguyen, Tongzheng Ren, Huy Nguyen, Litu Rout, Tan Nguyen, Nhat Ho |
| 2023 | ICLR | Latent Variable Representation for Reinforcement Learning. | Tongzheng Ren, Chenjun Xiao, Tianjun Zhang, Na Li, Zhaoran Wang, Sujay Sanghavi, Dale Schuurmans, Bo Dai |
| 2023 | ICLR | Spectral Decomposition Representation for Reinforcement Learning. | Tongzheng Ren, Tianjun Zhang, Lisa Lee, Joseph E. Gonzalez, Dale Schuurmans, Bo Dai |
| 2023 | UAI | Energy-based Predictive Representations for Partially Observed Reinforcement Learning. | Tianjun Zhang, Tongzheng Ren, Chenjun Xiao, Wenli Xiao, Joseph E. Gonzalez, Dale Schuurmans, Bo Dai |
| 2022 | AAAI | Policy Learning for Robust Markov Decision Process with a Mismatched Generative Model. | Jialian Li, Tongzheng Ren, Dong Yan, Hang Su, Jun Zhu |
| 2022 | AISTATS | Towards Statistical and Computational Complexities of Polyak Step Size Gradient Descent. | Tongzheng Ren, Fuheng Cui, Alexia Atsidakou, Sujay Sanghavi, Nhat Ho |
| 2022 | ICML | Linear Bandit Algorithms with Sublinear Time Complexity. | Shuo Yang, Tongzheng Ren, Sanjay Shakkottai, Eric Price, Inderjit S. Dhillon, Sujay Sanghavi |
| 2022 | ICML | Making Linear MDPs Practical via Contrastive Representation Learning. | Tianjun Zhang, Tongzheng Ren, Mengjiao Yang, Joseph Gonzalez, Dale Schuurmans, Bo Dai |
| 2022 | UAI | A free lunch from the noise: Provable and practical exploration for representation learning. | Tongzheng Ren, Tianjun Zhang, Csaba Szepesvri, Bo Dai |
| 2021 | AAAI | Learning Task-Distribution Reward Shaping with Meta-Learning. | Haosheng Zou, Tongzheng Ren, Dong Yan, Hang Su, Jun Zhu |
| 2021 | ACL | Unsupervised Out-of-Domain Detection via Pre-trained Transformers. | Keyang Xu, Tongzheng Ren, Shikun Zhang, Yihao Feng, Caiming Xiong |
| 2021 | CVPR | MaxUp: Lightweight Adversarial Training With Data Augmentation Improves Neural Network Training. | Chengyue Gong, Tongzheng Ren, Mao Ye, Qiang Liu |
| 2020 | ICLR | Lazy-CFR: fast and near-optimal regret minimization for extensive games with imperfect information. | Yichi Zhou, Tongzheng Ren, Jialian Li, Dong Yan, Jun Zhu |
| 2020 | ICML | Accountable Off-Policy Evaluation With Kernel Bellman Statistics. | Yihao Feng, Tongzheng Ren, Ziyang Tang, Qiang Liu |
| 2020 | UAI | Exploration Analysis in Finite-Horizon Turn-based Stochastic Games. | Jialian Li, Yichi Zhou, Tongzheng Ren, Jun Zhu |
| 2019 | ICLR | Function Space Particle Optimization for Bayesian Neural Networks. | Ziyu Wang, Tongzheng Ren, Jun Zhu, Bo Zhang |
| 2018 | IJCAI | Learning to Write Stylized Chinese Characters by Reading a Handful of Examples. | Danyang Sun, Tongzheng Ren, Chongxuan Li, Hang Su, Jun Zhu |