Learning to Write Stylized Chinese Characters by Reading a Handful of Examples. - Danyang Sun; Tongzheng Ren; Chongxuan Li; Hang Su 006; Jun Zhu 001 (IJCAI, 2018)

Lazy-CFR: a fast regret minimization algorithm for extensive games with imperfect information. - Yichi Zhou; Tongzheng Ren; Jialian Li; Dong Yan; Jun Zhu 001 (CoRR, 2018)

Learn a Robust Policy in Adversarial Games via Playing with an Expert Opponent. - Jialian Li; Tongzheng Ren; Hang Su 006; Jun Zhu 001 (AAMAS, 2019)

Function Space Particle Optimization for Bayesian Neural Networks. - Ziyu Wang 006; Tongzheng Ren; Jun Zhu 001; Bo Zhang 010 (ICLR (Poster), 2019)

Reward Shaping via Meta-Learning. - Haosheng Zou; Tongzheng Ren; Dong Yan; Hang Su 006; Jun Zhu 001 (CoRR, 2019)

Implicit Regularization of Normalization Methods. - Xiaoxia Wu; Edgar Dobriban; Tongzheng Ren; Shanshan Wu; Zhiyuan Li; Suriya Gunasekar; Rachel A. Ward; Qiang Liu 001 (CoRR, 2019)

Lazy-CFR: fast and near-optimal regret minimization for extensive games with imperfect information. - Yichi Zhou; Tongzheng Ren; Jialian Li; Dong Yan; Jun Zhu 001 (ICLR, 2020)

Accountable Off-Policy Evaluation With Kernel Bellman Statistics. - Yihao Feng; Tongzheng Ren; Ziyang Tang; Qiang Liu 001 (ICML, 2020)

Implicit Regularization and Convergence for Weight Normalization. - Xiaoxia Wu; Edgar Dobriban; Tongzheng Ren; Shanshan Wu; Zhiyuan Li; Suriya Gunasekar; Rachel A. Ward; Qiang Liu 001 (NeurIPS, 2020)

Stein Self-Repulsive Dynamics: Benefits From Past Samples. - Mao Ye 006; Tongzheng Ren; Qiang Liu 001 (NeurIPS, 2020)

Exploration Analysis in Finite-Horizon Turn-based Stochastic Games. - Jialian Li; Yichi Zhou; Tongzheng Ren; Jun Zhu 001 (UAI, 2020)

MaxUp: A Simple Way to Improve Generalization of Neural Network Training. - ChengYue Gong; Tongzheng Ren; Mao Ye 006; Qiang Liu 001 (CoRR, 2020)

Learning Task-Distribution Reward Shaping with Meta-Learning. - Haosheng Zou; Tongzheng Ren; Dong Yan; Hang Su 006; Jun Zhu 001 (AAAI, 2021)

Unsupervised Out-of-Domain Detection via Pre-trained Transformers. - Keyang Xu; Tongzheng Ren; Shikun Zhang; Yihao Feng; Caiming Xiong (ACL/IJCNLP (1), 2021)

MaxUp: Lightweight Adversarial Training With Data Augmentation Improves Neural Network Training. - Chengyue Gong; Tongzheng Ren; Mao Ye 006; Qiang Liu 001 (CVPR, 2021)

Nearly Horizon-Free Offline Reinforcement Learning. - Tongzheng Ren; Jialian Li; Bo Dai 001; Simon S. Du; Sujay Sanghavi (NeurIPS, 2021)

Scalable Quasi-Bayesian Inference for Instrumental Variable Regression. - Ziyu Wang 006; Yuhao Zhou; Tongzheng Ren; Jun Zhu 001 (NeurIPS, 2021)

Combinatorial Bandits without Total Order for Arms. - Shuo Yang; Tongzheng Ren; Inderjit S. Dhillon; Sujay Sanghavi (CoRR, 2021)

Policy Learning for Robust Markov Decision Process with a Mismatched Generative Model. - Jialian Li; Tongzheng Ren; Dong Yan; Hang Su 006; Jun Zhu 001 (AAAI, 2022)

Towards Statistical and Computational Complexities of Polyak Step Size Gradient Descent. - Tongzheng Ren; Fuheng Cui; Alexia Atsidakou; Sujay Sanghavi; Nhat Ho (AISTATS, 2022)

Linear Bandit Algorithms with Sublinear Time Complexity. - Shuo Yang; Tongzheng Ren; Sanjay Shakkottai; Eric Price 001; Inderjit S. Dhillon; Sujay Sanghavi (ICML, 2022)

Making Linear MDPs Practical via Contrastive Representation Learning. - Tianjun Zhang; Tongzheng Ren; Mengjiao Yang 001; Joseph Gonzalez 001; Dale Schuurmans; Bo Dai 001 (ICML, 2022)

A free lunch from the noise: Provable and practical exploration for representation learning. - Tongzheng Ren; Tianjun Zhang; Csaba Szepesvári; Bo Dai 001 (UAI, 2022)

Improving Computational Complexity in Statistical Models with Second-Order Information. - Tongzheng Ren; Jiacheng Zhuo; Sujay Sanghavi; Nhat Ho (CoRR, 2022)

An Exponentially Increasing Step-size for Parameter Estimation in Statistical Models. - Nhat Ho; Tongzheng Ren; Sujay Sanghavi; Purnamrita Sarkar; Rachel A. Ward (CoRR, 2022)

Beyond EM Algorithm on Over-specified Two-Component Location-Scale Gaussian Mixtures. - Tongzheng Ren; Fuheng Cui; Sujay Sanghavi; Nhat Ho (CoRR, 2022)

Efficient Forecasting of Large Scale Hierarchical Time Series via Multilevel Clustering. - Xing Han; Tongzheng Ren; Jing Hu; Joydeep Ghosh; Nhat Ho (CoRR, 2022)

Robustify Transformers with Robust Kernel Density Estimation. - Xing Han; Tongzheng Ren; Tan Minh Nguyen; Khai Nguyen; Joydeep Ghosh; Nhat Ho (CoRR, 2022)

Stochastic Nonlinear Control via Finite-dimensional Spectral Dynamic Embedding. - Tongzheng Ren; Zhaolin Ren; Na Li 002; Bo Dai 001 (CDC, 2023)

Hierarchical Sliced Wasserstein Distance. - Khai Nguyen; Tongzheng Ren; Huy Nguyen; Litu Rout; Tan Nguyen; Nhat Ho (ICLR, 2023)

Latent Variable Representation for Reinforcement Learning. - Tongzheng Ren; Chenjun Xiao; Tianjun Zhang; Na Li 002; Zhaoran Wang 001; Sujay Sanghavi; Dale Schuurmans; Bo Dai 001 (ICLR, 2023)

Spectral Decomposition Representation for Reinforcement Learning. - Tongzheng Ren; Tianjun Zhang; Lisa Lee; Joseph E. Gonzalez; Dale Schuurmans; Bo Dai 001 (ICLR, 2023)

Designing Robust Transformers using Robust Kernel Density Estimation. - Xing Han; Tongzheng Ren; Tan Nguyen; Khai Nguyen; Joydeep Ghosh; Nhat Ho (NeurIPS, 2023)

Markovian Sliced Wasserstein Distances: Beyond Independent Projections. - Khai Nguyen; Tongzheng Ren; Nhat Ho (NeurIPS, 2023)

Energy-based Predictive Representations for Partially Observed Reinforcement Learning. - Tianjun Zhang; Tongzheng Ren; Chenjun Xiao; Wenli Xiao; Joseph E. Gonzalez; Dale Schuurmans; Bo Dai 001 (UAI, 2023)

Improving Computational Complexity in Statistical Models with Local Curvature Information. - Pedram Akbarian; Tongzheng Ren; Jiacheng Zhuo; Sujay Sanghavi; Nhat Ho (ICML, 2024)

Provable Representation with Efficient Planning for Partially Observable Reinforcement Learning. - Hongming Zhang 012; Tongzheng Ren; Chenjun Xiao; Dale Schuurmans; Bo Dai 001 (ICML, 2024)

DeepSeek LLM: Scaling Open-Source Language Models with Longtermism. - Xiao Bi; Deli Chen; Guanting Chen 002; Shanhuang Chen; Damai Dai; Chengqi Deng; Honghui Ding; Kai Dong 003; Qiushi Du; Zhe Fu; Huazuo Gao; Kaige Gao; et al. (CoRR, 2024)

DeepSeek-VL: Towards Real-World Vision-Language Understanding. - Haoyu Lu; Wen Liu; Bo Zhang; Bingxuan Wang; Kai Dong 003; Bo Liu 039; Jingxiang Sun; Tongzheng Ren; Zhuoshu Li; Hao Yang; Yaofeng Sun; Chengqi Deng; et al. (CoRR, 2024)

Statistical and Computational Complexities of BFGS Quasi-Newton Method for Generalized Linear Models. - Qiujiang Jin; Tongzheng Ren; Nhat Ho; Aryan Mokhtari (Trans. Mach. Learn. Res., 2024)

Spectral Representation for Causal Estimation with Hidden Confounders. - Haotian Sun; Antoine Moulin; Tongzheng Ren; Arthur Gretton; Bo Dai 001 (AISTATS, 2025)