Tongzheng Ren

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 57

Top Topics

Reinforcement Learning

Imperfect Information

Kernel Density Estimation

Regret Minimization

Top Venues

Publications

Tongzheng Ren, Haotian Sun, Antoine Moulin, Arthur Gretton, Bo Dai
Spectral Representation for Causal Estimation with Hidden Confounders. CoRR (2024)
Qiujiang Jin, Tongzheng Ren, Nhat Ho, Aryan Mokhtari
Statistical and Computational Complexities of BFGS Quasi-Newton Method for Generalized Linear Models. Trans. Mach. Learn. Res. 2024 (2024)
Xiao Bi, Deli Chen, Guanting Chen, Shanhuang Chen, Damai Dai, Chengqi Deng, Honghui Ding, Kai Dong, Qiushi Du, Zhe Fu, Huazuo Gao, Kaige Gao, Wenjun Gao, Ruiqi Ge, Kang Guan, Daya Guo, Jianzhong Guo, Guangbo Hao, Zhewen Hao, Ying He, Wenjie Hu, Panpan Huang, Erhang Li, Guowei Li, Jiashi Li, Yao Li, Y. K. Li, Wenfeng Liang, Fangyun Lin, Alex X. Liu, Bo Liu, Wen Liu, Xiaodong Liu, Xin Liu, Yiyuan Liu, Haoyu Lu, Shanghao Lu, Fuli Luo, Shirong Ma, Xiaotao Nie, Tian Pei, Yishi Piao, Junjie Qiu, Hui Qu, Tongzheng Ren, Zehui Ren, Chong Ruan, Zhangli Sha, Zhihong Shao, Junxiao Song, Xuecheng Su, Jingxiang Sun, Yaofeng Sun, Minghui Tang, Bingxuan Wang, Peiyi Wang, Shiyu Wang, Yaohui Wang, Yongji Wang, Tong Wu, Y. Wu, Xin Xie, Zhenda Xie, Ziwei Xie, Yiliang Xiong, Hanwei Xu, R. X. Xu, Yanhong Xu, Dejian Yang, Yuxiang You, Shuiping Yu, Xingkai Yu, B. Zhang, Haowei Zhang, Lecong Zhang, Liyue Zhang, Mingchuan Zhang, Minghua Zhang, Wentao Zhang, Yichao Zhang, Chenggang Zhao, Yao Zhao, Shangyan Zhou, Shunfeng Zhou, Qihao Zhu, Yuheng Zou
DeepSeek LLM: Scaling Open-Source Language Models with Longtermism. CoRR (2024)
Haoyu Lu, Wen Liu, Bo Zhang, Bingxuan Wang, Kai Dong, Bo Liu, Jingxiang Sun, Tongzheng Ren, Zhuoshu Li, Hao Yang, Yaofeng Sun, Chengqi Deng, Hanwei Xu, Zhenda Xie, Chong Ruan
DeepSeek-VL: Towards Real-World Vision-Language Understanding. CoRR (2024)
Tongzheng Ren, Tianjun Zhang, Lisa Lee, Joseph E. Gonzalez, Dale Schuurmans, Bo Dai
Spectral Decomposition Representation for Reinforcement Learning. ICLR (2023)
Khai Nguyen, Tongzheng Ren, Nhat Ho
Markovian Sliced Wasserstein Distances: Beyond Independent Projections. NeurIPS (2023)
Tongzheng Ren, Zhaolin Ren, Na Li, Bo Dai
Stochastic Nonlinear Control via Finite-dimensional Spectral Dynamic Embedding. CoRR (2023)
Tianjun Zhang, Tongzheng Ren, Chenjun Xiao, Wenli Xiao, Joseph E. Gonzalez, Dale Schuurmans, Bo Dai
Energy-based Predictive Representations for Partially Observed Reinforcement Learning. UAI (2023)
Tongzheng Ren, Chenjun Xiao, Tianjun Zhang, Na Li, Zhaoran Wang, Sujay Sanghavi, Dale Schuurmans, Bo Dai
Latent Variable Representation for Reinforcement Learning. ICLR (2023)
Khai Nguyen, Tongzheng Ren, Nhat Ho
Markovian Sliced Wasserstein Distances: Beyond Independent Projections. CoRR (2023)
Tongzheng Ren, Zhaolin Ren, Na Li, Bo Dai
Stochastic Nonlinear Control via Finite-dimensional Spectral Dynamic Embedding. CDC (2023)
Xing Han, Tongzheng Ren, Tan Nguyen, Khai Nguyen, Joydeep Ghosh, Nhat Ho
Designing Robust Transformers using Robust Kernel Density Estimation. NeurIPS (2023)
Khai Nguyen, Tongzheng Ren, Huy Nguyen, Litu Rout, Tan Minh Nguyen, Nhat Ho
Hierarchical Sliced Wasserstein Distance. ICLR (2023)
Hongming Zhang, Tongzheng Ren, Chenjun Xiao, Dale Schuurmans, Bo Dai
Provable Representation with Efficient Planning for Partially Observable Reinforcement Learning. CoRR (2023)
Jialian Li, Tongzheng Ren, Dong Yan, Hang Su, Jun Zhu
Policy Learning for Robust Markov Decision Process with a Mismatched Generative Model. AAAI (2022)
Tongzheng Ren, Fuheng Cui, Sujay Sanghavi, Nhat Ho
Beyond EM Algorithm on Over-specified Two-Component Location-Scale Gaussian Mixtures. CoRR (2022)
Tongzheng Ren, Fuheng Cui, Alexia Atsidakou, Sujay Sanghavi, Nhat Ho
Towards Statistical and Computational Complexities of Polyak Step Size Gradient Descent. AISTATS (2022)
Xing Han, Tongzheng Ren, Tan Minh Nguyen, Khai Nguyen, Joydeep Ghosh, Nhat Ho
Robustify Transformers with Robust Kernel Density Estimation. CoRR (2022)
Tongzheng Ren, Jiacheng Zhuo, Sujay Sanghavi, Nhat Ho
Improving Computational Complexity in Statistical Models with Second-Order Information. CoRR (2022)
Tianjun Zhang, Tongzheng Ren, Mengjiao Yang, Joseph E. Gonzalez, Dale Schuurmans, Bo Dai
Making Linear MDPs Practical via Contrastive Representation Learning. CoRR (2022)
Tongzheng Ren, Tianjun Zhang, Lisa Lee, Joseph E. Gonzalez, Dale Schuurmans, Bo Dai
Spectral Decomposition Representation for Reinforcement Learning. CoRR (2022)
Khai Nguyen, Tongzheng Ren, Huy Nguyen, Litu Rout, Tan Nguyen, Nhat Ho
Hierarchical Sliced Wasserstein Distance. CoRR (2022)
Tongzheng Ren, Chenjun Xiao, Tianjun Zhang, Na Li, Zhaoran Wang, Sujay Sanghavi, Dale Schuurmans, Bo Dai
Latent Variable Representation for Reinforcement Learning. CoRR (2022)
Jialian Li, Tongzheng Ren, Dong Yan, Hang Su, Jun Zhu
Policy Learning for Robust Markov Decision Process with a Mismatched Generative Model. CoRR (2022)
Xing Han, Tongzheng Ren, Jing Hu, Joydeep Ghosh, Nhat Ho
Efficient Forecasting of Large Scale Hierarchical Time Series via Multilevel Clustering. CoRR (2022)
Tongzheng Ren, Tianjun Zhang, Csaba Szepesvári, Bo Dai
A free lunch from the noise: Provable and practical exploration for representation learning. UAI (2022)
Nhat Ho, Tongzheng Ren, Sujay Sanghavi, Purnamrita Sarkar, Rachel Ward
An Exponentially Increasing Step-size for Parameter Estimation in Statistical Models. CoRR (2022)
Tianjun Zhang, Tongzheng Ren, Mengjiao Yang, Joseph Gonzalez, Dale Schuurmans, Bo Dai
Making Linear MDPs Practical via Contrastive Representation Learning. ICML (2022)
Shuo Yang, Tongzheng Ren, Sanjay Shakkottai, Eric Price, Inderjit S. Dhillon, Sujay Sanghavi
Linear Bandit Algorithms with Sublinear Time Complexity. ICML (2022)
Tongzheng Ren, Tianjun Zhang, Csaba Szepesvári, Bo Dai
A Free Lunch from the Noise: Provable and Practical Exploration for Representation Learning. CoRR (2021)
Haosheng Zou, Tongzheng Ren, Dong Yan, Hang Su, Jun Zhu
Learning Task-Distribution Reward Shaping with Meta-Learning. AAAI (2021)
Tongzheng Ren, Jialian Li, Bo Dai, Simon S. Du, Sujay Sanghavi
Nearly Horizon-Free Offline Reinforcement Learning. CoRR (2021)
Shuo Yang, Tongzheng Ren, Sanjay Shakkottai, Eric Price, Inderjit S. Dhillon, Sujay Sanghavi
Linear Bandit Algorithms with Sublinear Time Complexity. CoRR (2021)
Chengyue Gong, Tongzheng Ren, Mao Ye, Qiang Liu
MaxUp: Lightweight Adversarial Training With Data Augmentation Improves Neural Network Training. CVPR (2021)
Shuo Yang, Tongzheng Ren, Inderjit S. Dhillon, Sujay Sanghavi
Combinatorial Bandits without Total Order for Arms. CoRR (2021)
Tongzheng Ren, Fuheng Cui, Alexia Atsidakou, Sujay Sanghavi, Nhat Ho
Towards Statistical and Computational Complexities of Polyak Step Size Gradient Descent. CoRR (2021)
Keyang Xu, Tongzheng Ren, Shikun Zhang, Yihao Feng, Caiming Xiong
Unsupervised Out-of-Domain Detection via Pre-trained Transformers. ACL/IJCNLP (1) (2021)
Ziyu Wang, Yuhao Zhou, Tongzheng Ren, Jun Zhu
Scalable Quasi-Bayesian Inference for Instrumental Variable Regression. CoRR (2021)
Tongzheng Ren, Jialian Li, Bo Dai, Simon S. Du, Sujay Sanghavi
Nearly Horizon-Free Offline Reinforcement Learning. NeurIPS (2021)
Keyang Xu, Tongzheng Ren, Shikun Zhang, Yihao Feng, Caiming Xiong
Unsupervised Out-of-Domain Detection via Pre-trained Transformers. CoRR (2021)
Ziyu Wang, Yuhao Zhou, Tongzheng Ren, Jun Zhu
Scalable Quasi-Bayesian Inference for Instrumental Variable Regression. NeurIPS (2021)
Xiaoxia Wu, Edgar Dobriban, Tongzheng Ren, Shanshan Wu, Zhiyuan Li, Suriya Gunasekar, Rachel Ward, Qiang Liu
Implicit Regularization and Convergence for Weight Normalization. NeurIPS (2020)
Yichi Zhou, Tongzheng Ren, Jialian Li, Dong Yan, Jun Zhu
Lazy-CFR: fast and near-optimal regret minimization for extensive games with imperfect information. ICLR (2020)
Yihao Feng, Tongzheng Ren, Ziyang Tang, Qiang Liu
Accountable Off-Policy Evaluation With Kernel Bellman Statistics. ICML (2020)
Jialian Li, Yichi Zhou, Tongzheng Ren, Jun Zhu
Exploration Analysis in Finite-Horizon Turn-based Stochastic Games. UAI (2020)
Mao Ye, Tongzheng Ren, Qiang Liu
Stein Self-Repulsive Dynamics: Benefits From Past Samples. NeurIPS (2020)
ChengYue Gong, Tongzheng Ren, Mao Ye, Qiang Liu
MaxUp: A Simple Way to Improve Generalization of Neural Network Training. CoRR (2020)
Yihao Feng, Tongzheng Ren, Ziyang Tang, Qiang Liu
Accountable Off-Policy Evaluation With Kernel Bellman Statistics. CoRR (2020)
Mao Ye, Tongzheng Ren, Qiang Liu
Stein Self-Repulsive Dynamics: Benefits From Past Samples. CoRR (2020)
Haosheng Zou, Tongzheng Ren, Dong Yan, Hang Su, Jun Zhu
Reward Shaping via Meta-Learning. CoRR (2019)
Jialian Li, Tongzheng Ren, Hang Su, Jun Zhu
Learn a Robust Policy in Adversarial Games via Playing with an Expert Opponent. AAMAS (2019)
Ziyu Wang, Tongzheng Ren, Jun Zhu, Bo Zhang
Function Space Particle Optimization for Bayesian Neural Networks. ICLR (Poster) (2019)
Xiaoxia Wu, Edgar Dobriban, Tongzheng Ren, Shanshan Wu, Zhiyuan Li, Suriya Gunasekar, Rachel Ward, Qiang Liu
Implicit Regularization of Normalization Methods. CoRR (2019)
Ziyu Wang, Tongzheng Ren, Jun Zhu, Bo Zhang
Function Space Particle Optimization for Bayesian Neural Networks. CoRR (2019)
Yichi Zhou, Tongzheng Ren, Jialian Li, Dong Yan, Jun Zhu
Lazy-CFR: a fast regret minimization algorithm for extensive games with imperfect information. CoRR (2018)
Danyang Sun, Tongzheng Ren, Chongxuan Li, Hang Su, Jun Zhu
Learning to Write Stylized Chinese Characters by Reading a Handful of Examples. IJCAI (2018)
Danyang Sun, Tongzheng Ren, Chongxuan Li, Jun Zhu, Hang Su
Learning to Write Stylized Chinese Characters by Reading a Handful of Examples. CoRR (2017)