Publications

Check out my Google Scholar.

2025

  1. ICLR
    Diffusing States and Matching Scores: A New Framework for Imitation Learning
    Runzhe Wu, Yiding Chen, Gokul Swamy, Kianté Brantley, and Wen Sun
    In The Thirteenth International Conference on Learning Representations, 2025
    arXiv
  2. ICML
    Convergence of Consistency Model with Multistep Sampling under General Data Assumptions
    Yiding Chen, Yiyi Zhang, Owen Oertell, and Wen Sun
    In Forty-second International Conference on Machine Learning, 2025
    arXiv
  3. ICML
    Collaborative Mean Estimation Among Heterogeneous Strategic Agents: Individual Rationality, Fairness, and Truthful Contribution
    Alex Clinton, Yiding Chen, Jerry Zhu, and Kirthevasan Kandasamy
    In Forty-second International Conference on Machine Learning, 2025
    arXiv
  4. arXiv
    Avoiding exp(R) scaling in RLHF through Preference-based Exploration
    Mingyu Chen, Yiding Chen, Wen Sun, and Xuezhou Zhang
    arXiv preprint arXiv:2502.00666, 2025
    arXiv
  5. arXiv
    Efficient Controllable Diffusion via Optimal Classifier Guidance
    Owen Oertell*, Shikun Sun*, Yiding Chen*, Jin Peng Zhou, Zhiyong Wang, and Wen Sun
    arXiv preprint arXiv:2505.21666, 2025
    arXiv
  6. arXiv
    Scaling Offline RL via Efficient and Expressive Shortcut Models
    Nicolas Espinosa-Dice, Yiyi Zhang, Yiding Chen, Bradley Guo, Owen Oertell, Gokul Swamy, Kiante Brantley, and Wen Sun
    arXiv preprint arXiv:2505.22866, 2025
    arXiv
  7. arXiv
    A Cramér-von Mises Approach to Incentivizing Truthful Data Sharing
    Alex Clinton, Thomas Zeng, Yiding Chen, Xiaojin Zhu, and Kirthevasan Kandasamy
    arXiv preprint arXiv:2506.07272, 2025
    arXiv

2024

  1. ICML
    Minimally Modifying a Markov Game to Achieve Any Nash Equilibrium and Value
    Young Wu, Jeremy McMahan, Yiding Chen, Yudong Chen, Jerry Zhu, and Qiaomin Xie
    In Forty-first International Conference on Machine Learning, 2024
    arXiv
  2. AAAI
    Exact policy recovery in offline rl with both heavy-tailed rewards and data corruption
    Yiding Chen, Xuezhou Zhang, Qiaomin Xie, and Xiaojin Zhu
    In Proceedings of the AAAI Conference on Artificial Intelligence, 2024

2023

  1. AISTATS
    Byzantine-robust online and offline distributed reinforcement learning
    Yiding Chen*, Xuezhou Zhang*, Kaiqing Zhang, Mengdi Wang, and Xiaojin Zhu
    In International Conference on Artificial Intelligence and Statistics, 2023
    arXiv
  2. NeurIPS
    Mechanism design for collaborative normal mean estimation
    Yiding Chen, Jerry Zhu, and Kirthevasan Kandasamy
    Advances in Neural Information Processing Systems, 2023
    Spotlight
    arXiv

2022

  1. AISTATS
    Corruption-robust offline reinforcement learning
    Xuezhou Zhang, Yiding Chen, Xiaojin Zhu, and Wen Sun
    In International Conference on Artificial Intelligence and Statistics, 2022
    arXiv
  2. arXiv
    The game of hidden rules: A new kind of benchmark challenge for machine learning
    Eric Pulick, Shubham Bharti, Yiding Chen, Vladimir Menkov, Yonatan Mintz, Paul Kantor, and Vicki M Bier
    arXiv preprint arXiv:2207.10218, 2022
    arXiv

2021

  1. ICML
    Robust policy gradient against strong data corruption
    Xuezhou Zhang, Yiding Chen, Xiaojin Zhu, and Wen Sun
    In International Conference on Machine Learning, 2021
    arXiv

2020

  1. AAAI
    Optimal attack against autoregressive models by manipulating the environment
    Yiding Chen and Xiaojin Zhu
    In Proceedings of the AAAI conference on artificial intelligence, 2020
    arXiv

2019

  1. arXiv
    Error lower bounds of constant step-size stochastic gradient descent
    Zhiyan Ding, Yiding Chen, Qin Li, and Xiaojin Zhu
    arXiv preprint arXiv:1910.08212, 2019
    arXiv