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Research Interests
Integrative data analysis: multi-task learning, meta-learning and transfer learning;
Latent variable models and representation learning;
Non-convex optimization and distributed optimization.
Papers and Preprints
(\(\alpha\)-\(\beta\): author names are sorted alphabetically; \(\dagger\): student/postdoc supervised.)
2025
Uncertainty Quantification for LLM-Based Survey Simulations.
Chengpiao Huang\(\dagger\), Yuhang Wu, Kaizheng Wang
arXiv preprint arXiv:2502.17773, 2025. Code
Transfer Learning of CATE with Kernel Ridge Regression.
Seok-Jin Kim\(\dagger\), Hongjie Liu, Molei Liu, Kaizheng Wang
arXiv preprint arXiv:2502.11331, 2025.
2024
A Particle Algorithm for Mean-Field Variational Inference.
Qiang Du, Kaizheng Wang, Edith Zhang, Chenyang Zhong (\(\alpha\)-\(\beta\))
arXiv preprint arXiv:2412.20385, 2024.
Localized Exploration in Contextual Dynamic Pricing Achieves Dimension-Free Regret.
Jinhang Chai, Yaqi Duan, Jianqing Fan, Kaizheng Wang (\(\alpha\)-\(\beta\))
arXiv preprint arXiv:2412.19252, 2024.
Adaptive Transfer Clustering: A Unified Framework.
Yuqi Gu, Zhongyuan Lyu\(\dagger\), Kaizheng Wang (\(\alpha\)-\(\beta\))
arXiv preprint arXiv:2410.21263, 2024. Code
Distribution-Free Predictive Inference under Unknown Temporal Drift.
Elise Han\(\dagger\), Chengpiao Huang\(\dagger\), Kaizheng Wang (\(\alpha\)-\(\beta\))
arXiv preprint arXiv:2406.06516, 2024. Code
Model Assessment and Selection under Temporal Distribution Shift.
Elise Han\(\dagger\), Chengpiao Huang\(\dagger\), Kaizheng Wang (\(\alpha\)-\(\beta\))
International Conference on Machine Learning, 2024.
arXiv Code
2023
A Stability Principle for Learning under Non-Stationarity.
Chengpiao Huang\(\dagger\), Kaizheng Wang (\(\alpha\)-\(\beta\))
Operations Research (accepted), 2025+.
arXiv preprint arXiv:2310.18304, 2023. Code
Pseudo-Labeling for Kernel Ridge Regression under Covariate Shift.
Kaizheng Wang
Junior Researcher Award, 2024 ICSA China Conference.
arXiv preprint arXiv:2302.10160, 2023. Talk Code
Learning Gaussian Mixtures Using the Wasserstein-Fisher-Rao Gradient Flow.
Yuling Yan\(*\), Kaizheng Wang\(*\), Philippe Rigollet (\(*\) = equal contribution)
Annals of Statistics 52(4): 1774-1795, 2024.
arXiv
2022
Variable Clustering via Distributionally Robust Nodewise Regression.
Kaizheng Wang, Xiao Xu, Xun Yu Zhou (\(\alpha\)-\(\beta\))
arXiv preprint arXiv:2212.07944, 2022.
Adaptive Data Fusion for Multi-Task Non-Smooth Optimization.
Henry Lam, Kaizheng Wang, Yuhang Wu\(\dagger\), Yichen Zhang (\(\alpha\)-\(\beta\))
arXiv preprint arXiv:2210.12334, 2022.
Discussion of ‘Vintage Factor Analysis with Varimax Performs Statistical Inference’ by Rohe & Zeng.
Kaizheng Wang
Journal of the Royal Statistical Society Series B: Statistical Methodology 85(4): 1068, 2023.
Adaptive and Robust Multi-Task Learning
Yaqi Duan, Kaizheng Wang (\(\alpha\)-\(\beta\))
Annals of Statistics 51(5): 2015-2039, 2023.
arXiv Code
2021
Clustering a Mixture of Gaussians with Unknown Covariance
Damek Davis, Mateo Díaz, Kaizheng Wang (\(\alpha\)-\(\beta\))
Bernoulli 31 (3): 2105-2126, 2025.
arXiv preprint arXiv:2110.01602, 2021.
Modern Data Modeling: Cross-Fertilization of the Two Cultures
Jianqing Fan, Cong Ma, Kaizheng Wang, Ziwei Zhu (\(\alpha\)-\(\beta\))
Observational Studies 7 (1): 65-76, 2021.
2020
Comment on “A Tuning-Free Robust and Efficient Approach to High-Dimensional Regression”
Jianqing Fan, Cong Ma, Kaizheng Wang (\(\alpha\)-\(\beta\))
Journal of the American Statistical Association 115 (532): 1720-1725, 2020.
An \(\ell_p\) Theory of PCA and Spectral Clustering
Emmanuel Abbe, Jianqing Fan, Kaizheng Wang (\(\alpha\)-\(\beta\))
Annals of Statistics 50 (4): 2359-2385, 2022.
Frontiers of Science Award in Mathematics, 2024 International Congress of Basic Science.
Presented by Jianqing Fan at the IMS Le Cam Lecture at the 2021 Joint Statistical Meetings.
arXiv
Efficient Clustering for Stretched Mixtures: Landscape and Optimality
Kaizheng Wang, Yuling Yan, Mateo Díaz
Neural Information Processing Systems, 2020.
arXiv
2019
Communication-Efficient Accurate Statistical Estimation
Jianqing Fan, Yongyi Guo, Kaizheng Wang (\(\alpha\)-\(\beta\))
Journal of American Statistical Association 118 (542): 1000-1010, 2023.
arXiv
2018
Robust High Dimensional Factor Models with Applications to Statistical Machine Learning
Jianqing Fan, Kaizheng Wang, Yiqiao Zhong, Ziwei Zhu (\(\alpha\)-\(\beta\))
Statistical Science 36 (2): 303-327, 2021.
arXiv
2017
Implicit Regularization in Nonconvex Statistical Estimation: Gradient Descent Converges Linearly for Phase Retrieval, Matrix Completion and Blind Deconvolution
Cong Ma, Kaizheng Wang, Yuejie Chi, Yuxin Chen
Foundations of Computational Mathematics 20 (3): 451–632, 2020.
SIAM Activity Group on Imaging Science Best Paper Prize, 2024.
Short version accepted by International Conference on Machine Learning, 2018.
arXiv
Entrywise Eigenvector Analysis of Random Matrices with Low Expected Rank
Emmanuel Abbe, Jianqing Fan, Kaizheng Wang, Yiqiao Zhong (\(\alpha\)-\(\beta\))
Annals of Statistics 48 (3): 1452-1474, 2020.
arXiv
Spectral Method and Regularized MLE are both Optimal for Top-K Ranking
Yuxin Chen, Jianqing Fan, Cong Ma, Kaizheng Wang (\(\alpha\)-\(\beta\))
Annals of Statistics 47 (4): 2204-2235, 2019.
arXiv
Distributed Estimation of Principal Eigenspaces
Jianqing Fan, Dong Wang, Kaizheng Wang, Ziwei Zhu (\(\alpha\)-\(\beta\))
Annals of Statistics 47 (6): 3009-3031, 2019.
arXiv
2016
Factor-Adjusted Regularized Model Selection
Jianqing Fan, Yuan Ke, Kaizheng Wang (\(\alpha\)-\(\beta\))
Journal of Econometrics 216 (1): 71-85, 2020.
arXiv
2015
2014
Notes
A Similarity Measure Between Functions with Applications to Statistical Learning and Optimization
Chengpiao Huang\(\dagger\), Kaizheng Wang
arXiv preprint arXiv:2501.08317, 2025.
Some Compact Notations for Concentration Inequalities and User-Friendly Results
Kaizheng Wang
arXiv preprint arXiv:1912.13463, 2019.
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