Tongzheng Ren

About me

I am a second year PhD student in the Department of Computer Science at the University of Texas at Austin. I am fortunate to be advised by Prof. Sujay Sanghavi. I also worked with Prof. Qiang Liu during my first year at UT. My research focus on the theoritical aspects of machine learning, including but not restricted to optimization, statistics and online learning.

Before moving to Austin, I received the B.S. degree in Fundamental Science and Double B.S. degree in Mathematics and Applied Mathematics from Tsinghua University in 2018. During the undergraduate study, I was fortunate to work with Prof. Jun Zhu on different topics in Machine Learning. See my CV for detailed information.

Publications

Peer Reviewed Conference

  • Stein Self-Repulsive Dynamics: Benefits from Past Samples. [arXiv]
    Mao Ye*, Tongzheng Ren*, Qiang Liu (* Equal Contribution)
    Advances in Neural Information Processing Systems (NeurIPS) 2020

  • Implicit Regularization and Convergence for Weight Normalization. [arXiv]
    Xiaoxia Wu*, Edgar Dobriban*, Tongzheng Ren*, Shanshan Wu*, Zhiyuan Li, Suriya Gunasekar, Rachel Ward, Qiang Liu (* Equal Contribution)
    Advances in Neural Information Processing Systems (NeurIPS) 2020

  • Accountable Off-Policy Evaluation via a Kernelized Bellman Statistics. [arXiv] [ICML version]
    Yihao Feng*, Tongzheng Ren*, Ziyang Tang*, Qiang Liu (* Equal Contribution)
    International Conference on Machine Learning (ICML) 2020

  • Exploration Analysis in Finite-Horizon Turn-based Stochastic Games. [UAI version]
    Jialian Li, Yichi Zhou, Tongzheng Ren, Jun Zhu
    Conference on Uncertainty in Artificial Intelligence (UAI) 2020.

  • Lazy-CFR: a fast regret minimization algorithm for extensive games with imperfect information. [arXiv] [ICLR version]
    Yichi Zhou, Tongzheng Ren, Jialian Li, Dong Yan, Jun Zhu
    International Conference on Learning Representation (ICLR) 2020

  • Learn a Robust Policy in Adversarial Games via Playing with an Expert Opponent. [AAMAS version]
    Jialian Li, Tongzheng Ren, Hang Su, Jun Zhu
    International Conference on Autonomous Agents and MultiAgent Systems (AAMAS) 2019 (Extended Abstract)

  • Function Space Particle Optimization for Bayesian Neural Networks. [arXiv] [ICLR version]
    Ziyu Wang, Tongzheng Ren, Jun Zhu, Bo Zhang
    International Conference on Learning Representation (ICLR) 2019

  • Learning to write stylized Chinese Charaters by Reading a Handful of Examples. [arXiv] [IJCAI version]
    Danyang Sun*. Tongzheng Ren*, Chongxuan Li, Hang Su, Jun Zhu (* Equal Contribution)
    International Joint Conference on Artificial Intelligence (IJCAI) 2018

Preprint

  • MaxUp: A Simple Way to Improve Generalization of Neural Network Training [arXiv]
    Chengyue Gong*, Tongzheng Ren*, Mao Ye, Qiang Liu (* Equal Contribution)

  • Reward Shaping via Meta-Learning [arXiv]
    Haosheng Zou*, Tongzheng Ren*, Dong Yan, Hang Su, Jun Zhu (* Equal Contribution)

Professional Activities

  • Conference Review: NeurIPS, ICLR, AAAI, AISTATS

  • Journal Review: JMLR, TNNLS