Publications

^* indicates alphabetical author order or equal contribution.

You can also find my articles on Google Scholar.

1. Weak Convergence Rates for Partial-Sum Processes of Nonlinear Stochastic Approximation
   Xiang Li^*, Jiadong Liang^*, and Zhihua Zhang^*

2. Optimal training-conditional regret for online conformal prediction
   Jiadong Liang, Zhimei Ren, and Yuxin Chen
   revision invited by Annals of Statistics

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

4. Decoupled Functional Central Limit Theorems for Two-Time-Scale Stochastic Approximation
   Yuze Han^*, Xiang Li^*, Jiadong Liang^*, and Zhihua Zhang^*
   Mathematics of Operations Research (2026)

5. Asymptotic Time-Uniform Inference for Parameters in Averaged Stochastic Approximation
   Chuhan Xie, Kaicheng Jin, Jiadong Liang, and Zhihua Zhang

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

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

8. Stochastic Approximation MCMC, Online Inference, and Applications in Optimization of Queueing Systems
   Xiang Li^*, Jiadong Liang^*, Xinyun Chen, and Zhihua Zhang
   Operations Research (2026)

9. 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)

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

11. 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%)

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

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

14. 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)