Publications

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

2. Decoupled Functional Central Limit Theorems for Two-Time-Scale Stochastic Approximation
   Yuze Han, Xiang Li, Jiadong Liang, and Zhihua Zhang
   Major revision at Mathematics of Operation Research

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

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

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

6. 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)

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

8. 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%)

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

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

11. 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)