You can also find my articles on Google Scholar.

  1. Optimal training-conditional regret for online conformal prediction
    Jiadong Liang, Zhimei Ren, and Yuxin Chen

  2. Low-dimensional adaptation of diffusion models: Convergence in total variation
    Jiadong Liang, Zhihan Huang, and Yuxin Chen
    Conference on Learning Theory (COLT) (2025)

  3. Decoupled Functional Central Limit Theorems for Two-Time-Scale Stochastic Approximation
    Yuze Han, Xiang Li, Jiadong Liang, and Zhihua Zhang
    Accepted by Mathematics of Operations Research (MOR)

  4. Estimation and Inference in Distributional Reinforcement Learning
    Liangyu Zhang, Yang Peng, Jiadong Liang, Wenhao Yang, and Zhihua Zhang
    Annals of Statistics (2025)

  5. Gradient Tracking for High Dimensional Federated Optimization
    Jiadong Liang, Yang Peng, and Zhihua Zhang

  6. Stochastic Approximation MCMC, Online Inference, and Applications in Optimization of Queueing Systems
    Xiang Li , Jiadong Liang ,Xinyun Chen, and Zhihua Zhang
    Operation Research (2026+)

  7. A statistical analysis of Polyak-Ruppert averaged Q-learning
    Xiang Li, Wenhao Yang, Jiadong Liang, Zhihua Zhang, and Michel I. Jordan
    Artificial Intelligence and Statistics Conference (AISTATS) (2025)

  8. Online statistical inference for nonlinear stochastic approximation with Markovian data
    Xiang Li, Jiadong Liang, and Zhihua Zhang

  9. Asymptotic behaviors of projected stochastic approximation: a jump diffusion perspective
    Jiadong Liang, Yuze Han, Xiang Li, and Zhihua Zhang
    Conference on Neural Information Processing Systems (Neurips) (2022), Spotlight (top 2%)

  10. Statistical estimation and inference via local sgd
    Xiang Li, Jiadong Liang, Xiangyu Chang, and Zhihua Zhang
    Conference on Learning Theory (COLT) (2022)

  11. Intervention generative adversarial networks
    Jiadong Liang, Liangyu Zhang, Cheng Zhang, and Zhihua Zhang

  12. Lipschitz generative adversarial nets
    Zhiming Zhou, Jiadong Liang, Yuxuan Song, Lantao Yu, Hongwei Wang, Weinan Zhang, Yong Yu, and Zhihua Zhang
    International Conference on Machine Learning (ICML) (2019)