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Tongzheng Ren
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2020 – today
- 2024
- [j1]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) - [c27]Pedram Akbarian, Tongzheng Ren, Jiacheng Zhuo, Sujay Sanghavi, Nhat Ho:
Improving Computational Complexity in Statistical Models with Local Curvature Information. ICML 2024 - [c26]Hongming Zhang, Tongzheng Ren, Chenjun Xiao, Dale Schuurmans, Bo Dai:
Provable Representation with Efficient Planning for Partially Observable Reinforcement Learning. ICML 2024 - [i31]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 abs/2401.02954 (2024) - [i30]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 abs/2403.05525 (2024) - [i29]Tongzheng Ren, Haotian Sun, Antoine Moulin, Arthur Gretton, Bo Dai:
Spectral Representation for Causal Estimation with Hidden Confounders. CoRR abs/2407.10448 (2024) - 2023
- [c25]Tongzheng Ren, Zhaolin Ren, Na Li, Bo Dai:
Stochastic Nonlinear Control via Finite-dimensional Spectral Dynamic Embedding. CDC 2023: 795-800 - [c24]Khai Nguyen, Tongzheng Ren, Huy Nguyen, Litu Rout, Tan Minh Nguyen, Nhat Ho:
Hierarchical Sliced Wasserstein Distance. ICLR 2023 - [c23]Tongzheng Ren, Chenjun Xiao, Tianjun Zhang, Na Li, Zhaoran Wang, Sujay Sanghavi, Dale Schuurmans, Bo Dai:
Latent Variable Representation for Reinforcement Learning. ICLR 2023 - [c22]Tongzheng Ren, Tianjun Zhang, Lisa Lee, Joseph E. Gonzalez, Dale Schuurmans, Bo Dai:
Spectral Decomposition Representation for Reinforcement Learning. ICLR 2023 - [c21]Xing Han, Tongzheng Ren, Tan Nguyen, Khai Nguyen, Joydeep Ghosh, Nhat Ho:
Designing Robust Transformers using Robust Kernel Density Estimation. NeurIPS 2023 - [c20]Khai Nguyen, Tongzheng Ren, Nhat Ho:
Markovian Sliced Wasserstein Distances: Beyond Independent Projections. NeurIPS 2023 - [c19]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: 2477-2487 - [i28]Khai Nguyen, Tongzheng Ren, Nhat Ho:
Markovian Sliced Wasserstein Distances: Beyond Independent Projections. CoRR abs/2301.03749 (2023) - [i27]Tongzheng Ren, Zhaolin Ren, Na Li, Bo Dai:
Stochastic Nonlinear Control via Finite-dimensional Spectral Dynamic Embedding. CoRR abs/2304.03907 (2023) - [i26]Hongming Zhang, Tongzheng Ren, Chenjun Xiao, Dale Schuurmans, Bo Dai:
Provable Representation with Efficient Planning for Partially Observable Reinforcement Learning. CoRR abs/2311.12244 (2023) - 2022
- [c18]Jialian Li, Tongzheng Ren, Dong Yan, Hang Su, Jun Zhu:
Policy Learning for Robust Markov Decision Process with a Mismatched Generative Model. AAAI 2022: 7417-7425 - [c17]Tongzheng Ren, Fuheng Cui, Alexia Atsidakou, Sujay Sanghavi, Nhat Ho:
Towards Statistical and Computational Complexities of Polyak Step Size Gradient Descent. AISTATS 2022: 3930-3961 - [c16]Shuo Yang, Tongzheng Ren, Sanjay Shakkottai, Eric Price, Inderjit S. Dhillon, Sujay Sanghavi:
Linear Bandit Algorithms with Sublinear Time Complexity. ICML 2022: 25241-25260 - [c15]Tianjun Zhang, Tongzheng Ren, Mengjiao Yang, Joseph Gonzalez, Dale Schuurmans, Bo Dai:
Making Linear MDPs Practical via Contrastive Representation Learning. ICML 2022: 26447-26466 - [c14]Tongzheng Ren, Tianjun Zhang, Csaba Szepesvári, Bo Dai:
A free lunch from the noise: Provable and practical exploration for representation learning. UAI 2022: 1686-1696 - [i25]Tongzheng Ren, Jiacheng Zhuo, Sujay Sanghavi, Nhat Ho:
Improving Computational Complexity in Statistical Models with Second-Order Information. CoRR abs/2202.04219 (2022) - [i24]Jialian Li, Tongzheng Ren, Dong Yan, Hang Su, Jun Zhu:
Policy Learning for Robust Markov Decision Process with a Mismatched Generative Model. CoRR abs/2203.06587 (2022) - [i23]Nhat Ho, Tongzheng Ren, Sujay Sanghavi, Purnamrita Sarkar, Rachel A. Ward:
An Exponentially Increasing Step-size for Parameter Estimation in Statistical Models. CoRR abs/2205.07999 (2022) - [i22]Tongzheng Ren, Fuheng Cui, Sujay Sanghavi, Nhat Ho:
Beyond EM Algorithm on Over-specified Two-Component Location-Scale Gaussian Mixtures. CoRR abs/2205.11078 (2022) - [i21]Xing Han, Tongzheng Ren, Jing Hu, Joydeep Ghosh, Nhat Ho:
Efficient Forecasting of Large Scale Hierarchical Time Series via Multilevel Clustering. CoRR abs/2205.14104 (2022) - [i20]Tianjun Zhang, Tongzheng Ren, Mengjiao Yang, Joseph E. Gonzalez, Dale Schuurmans, Bo Dai:
Making Linear MDPs Practical via Contrastive Representation Learning. CoRR abs/2207.07150 (2022) - [i19]Tongzheng Ren, Tianjun Zhang, Lisa Lee, Joseph E. Gonzalez, Dale Schuurmans, Bo Dai:
Spectral Decomposition Representation for Reinforcement Learning. CoRR abs/2208.09515 (2022) - [i18]Khai Nguyen, Tongzheng Ren, Huy Nguyen, Litu Rout, Tan Nguyen, Nhat Ho:
Hierarchical Sliced Wasserstein Distance. CoRR abs/2209.13570 (2022) - [i17]Xing Han, Tongzheng Ren, Tan Minh Nguyen, Khai Nguyen, Joydeep Ghosh, Nhat Ho:
Robustify Transformers with Robust Kernel Density Estimation. CoRR abs/2210.05794 (2022) - [i16]Tongzheng Ren, Chenjun Xiao, Tianjun Zhang, Na Li, Zhaoran Wang, Sujay Sanghavi, Dale Schuurmans, Bo Dai:
Latent Variable Representation for Reinforcement Learning. CoRR abs/2212.08765 (2022) - 2021
- [c13]Haosheng Zou, Tongzheng Ren, Dong Yan, Hang Su, Jun Zhu:
Learning Task-Distribution Reward Shaping with Meta-Learning. AAAI 2021: 11210-11218 - [c12]Keyang Xu, Tongzheng Ren, Shikun Zhang, Yihao Feng, Caiming Xiong:
Unsupervised Out-of-Domain Detection via Pre-trained Transformers. ACL/IJCNLP (1) 2021: 1052-1061 - [c11]Chengyue Gong, Tongzheng Ren, Mao Ye, Qiang Liu:
MaxUp: Lightweight Adversarial Training With Data Augmentation Improves Neural Network Training. CVPR 2021: 2474-2483 - [c10]Ziyu Wang, Yuhao Zhou, Tongzheng Ren, Jun Zhu:
Scalable Quasi-Bayesian Inference for Instrumental Variable Regression. NeurIPS 2021: 10469-10482 - [c9]Tongzheng Ren, Jialian Li, Bo Dai, Simon S. Du, Sujay Sanghavi:
Nearly Horizon-Free Offline Reinforcement Learning. NeurIPS 2021: 15621-15634 - [i15]Shuo Yang, Tongzheng Ren, Sanjay Shakkottai, Eric Price, Inderjit S. Dhillon, Sujay Sanghavi:
Linear Bandit Algorithms with Sublinear Time Complexity. CoRR abs/2103.02729 (2021) - [i14]Shuo Yang, Tongzheng Ren, Inderjit S. Dhillon, Sujay Sanghavi:
Combinatorial Bandits without Total Order for Arms. CoRR abs/2103.02741 (2021) - [i13]Tongzheng Ren, Jialian Li, Bo Dai, Simon S. Du, Sujay Sanghavi:
Nearly Horizon-Free Offline Reinforcement Learning. CoRR abs/2103.14077 (2021) - [i12]Keyang Xu, Tongzheng Ren, Shikun Zhang, Yihao Feng, Caiming Xiong:
Unsupervised Out-of-Domain Detection via Pre-trained Transformers. CoRR abs/2106.00948 (2021) - [i11]Ziyu Wang, Yuhao Zhou, Tongzheng Ren, Jun Zhu:
Scalable Quasi-Bayesian Inference for Instrumental Variable Regression. CoRR abs/2106.08750 (2021) - [i10]Tongzheng Ren, Fuheng Cui, Alexia Atsidakou, Sujay Sanghavi, Nhat Ho:
Towards Statistical and Computational Complexities of Polyak Step Size Gradient Descent. CoRR abs/2110.07810 (2021) - [i9]Tongzheng Ren, Tianjun Zhang, Csaba Szepesvári, Bo Dai:
A Free Lunch from the Noise: Provable and Practical Exploration for Representation Learning. CoRR abs/2111.11485 (2021) - 2020
- [c8]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 - [c7]Yihao Feng, Tongzheng Ren, Ziyang Tang, Qiang Liu:
Accountable Off-Policy Evaluation With Kernel Bellman Statistics. ICML 2020: 3102-3111 - [c6]Xiaoxia Wu, Edgar Dobriban, Tongzheng Ren, Shanshan Wu, Zhiyuan Li, Suriya Gunasekar, Rachel A. Ward, Qiang Liu:
Implicit Regularization and Convergence for Weight Normalization. NeurIPS 2020 - [c5]Mao Ye, Tongzheng Ren, Qiang Liu:
Stein Self-Repulsive Dynamics: Benefits From Past Samples. NeurIPS 2020 - [c4]Jialian Li, Yichi Zhou, Tongzheng Ren, Jun Zhu:
Exploration Analysis in Finite-Horizon Turn-based Stochastic Games. UAI 2020: 201-210 - [i8]ChengYue Gong, Tongzheng Ren, Mao Ye, Qiang Liu:
MaxUp: A Simple Way to Improve Generalization of Neural Network Training. CoRR abs/2002.09024 (2020) - [i7]Mao Ye, Tongzheng Ren, Qiang Liu:
Stein Self-Repulsive Dynamics: Benefits From Past Samples. CoRR abs/2002.09070 (2020) - [i6]Yihao Feng, Tongzheng Ren, Ziyang Tang, Qiang Liu:
Accountable Off-Policy Evaluation With Kernel Bellman Statistics. CoRR abs/2008.06668 (2020)
2010 – 2019
- 2019
- [c3]Jialian Li, Tongzheng Ren, Hang Su, Jun Zhu:
Learn a Robust Policy in Adversarial Games via Playing with an Expert Opponent. AAMAS 2019: 2096-2098 - [c2]Ziyu Wang, Tongzheng Ren, Jun Zhu, Bo Zhang:
Function Space Particle Optimization for Bayesian Neural Networks. ICLR (Poster) 2019 - [i5]Haosheng Zou, Tongzheng Ren, Dong Yan, Hang Su, Jun Zhu:
Reward Shaping via Meta-Learning. CoRR abs/1901.09330 (2019) - [i4]Ziyu Wang, Tongzheng Ren, Jun Zhu, Bo Zhang:
Function Space Particle Optimization for Bayesian Neural Networks. CoRR abs/1902.09754 (2019) - [i3]Xiaoxia Wu, Edgar Dobriban, Tongzheng Ren, Shanshan Wu, Zhiyuan Li, Suriya Gunasekar, Rachel A. Ward, Qiang Liu:
Implicit Regularization of Normalization Methods. CoRR abs/1911.07956 (2019) - 2018
- [c1]Danyang Sun, Tongzheng Ren, Chongxuan Li, Hang Su, Jun Zhu:
Learning to Write Stylized Chinese Characters by Reading a Handful of Examples. IJCAI 2018: 920-927 - [i2]Yichi Zhou, Tongzheng Ren, Jialian Li, Dong Yan, Jun Zhu:
Lazy-CFR: a fast regret minimization algorithm for extensive games with imperfect information. CoRR abs/1810.04433 (2018) - 2017
- [i1]Danyang Sun, Tongzheng Ren, Chongxuan Li, Jun Zhu, Hang Su:
Learning to Write Stylized Chinese Characters by Reading a Handful of Examples. CoRR abs/1712.06424 (2017)
Coauthor Index
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last updated on 2024-09-09 01:15 CEST by the dblp team
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