发表的论文(Published Papers):
Representative Papers
Zengjing Chen, Xiaodong Yan* and Guodong Zhang, 2023. (Top)
Strategic two-sample test via two-armed bandit process
Journal of the Royal Statistical Society Series B: Statistical Methodology, 85,1271–1298(Reinforcement Learning)
Niansheng Tang#, Xiaodong Yan# and Xingqiu Zhao#, 2020. (Top)
Penalized generalized empirical likelihood with a diverging number of general estimating equations for censored data
Annals of Statistics，48(1), 607-627. (High Dimensional Data)
Jinhan Xie, Yuanyuan Lin, Xiaodong Yan and Niansheng Tang, 2019. (Top)
Categorical-adaptive variable screening for ultra-high dimensional heterogeneous categorical data
Journal of the American Statistical Association. 115(530), 747-760. (High Dimensional Data)
Niansheng Tang#, Xiaodong Yan# and Puying Zhao#,2018. (Top)
Exponentially tilted likelihood inference for growing dimensional unconditional moment models
Journal of Econometrics, 202(1), 57-74. (High Dimensional Data)
Jinhan Xie#, Xiaodong Yan#, Bei Jiang, Linglong Kong, 2023. (Top)
Statistical inference for smoothed quantile regression with streaming data
Journal of Econometrics, forthcoming， co-first author (Online Learning)
Xiaodong Yan, Guosheng Yin and Xingqiu Zhao, 2021.
Subgroup analysis in censored linear regression
Statistica Sinica, 31, 1027-1054. (Multi-source Heterogeneous Data, Censored Data)
Jian Huang , Yuling Jiao , Wei Wang, Xiaodong Yan*, Liping Zhu, 2023.
Integrative analysis for high-dimensional stratified models
Statistica Sinica, 33, 1533-1553. (Multi-source Heterogeneous Data, High Dimensional Data)
Jinhan Xie, Xiaodong Yan, Niansheng Tang, 2021.
A model-averaging method for high-dimensional regression with missing responses at random
Statistica Sinica, 31, 1005-1026. (Ensemble Learning)
Big Complex Data
Xinfeng Yang, Xiaodong Yan* and Jian Huang*, 2019.
High-dimensional integrative analysis with homogeneity and sparsity recovery
Journal of Multivariate Analysis, 174, 104529. (Multi-source Heterogeneous Data, High Dimensional Data)
Xiaoxia Li, Niansheng Tang, Jinhan Xie and Xiaodong Yan, 2020.
A nonparametric feature screening method for ultrahigh-dimensional missing data
Computational Statistics and Data Analysis, 142, 106828. (High Dimensional Data)
Niansheng Tang, Linli Xia, Xiaodong Yan, 2019.
Feature screening in ultrahigh-dimensional partially linear models with missing responses at random
Computational Statistics & Data Analysis, 133, 208–227. (High Dimensional Data，Missing Data)
Xiaodong Yan, Niansheng Tang,Jinhan Xie, Xianwen Ding, Zhiqiang Wang, 2018.
Fused mean–variance filter for feature screening
Computational Statistics & Data Analysis, 122, 18-32. (High Dimensional Data)
Yangming Ou, Xiaodong Yan,Ji Chen, Niansheng Tang and Xinyuan Song, 2017.
Bayesian local influence of structural equation models
Computational Statistics & Data Analysis, 111, 102-115.
Xinfeng Yang and Xiaodong Yan*, 2020.
Mechanism and a new algorithm for nonconvex clustering
Journal of Statistical Computation and Simulation, 90(4),719-746. (Multi-source Heterogeneous Data)
Yan Zhou, Li Zhang, Jinfeng Xu, Jun Zhang* and Xiaodong Yan*, 2021.
Category encoding method to select feature genes for the classification of bulk and single-cell RNA-seq data
Statistics in Medicine, 40(18):4077-4089. (High Dimensional Data)
Xiaodong Yan, Hongni Wang, Yanqiu Zhou, Jingxin Yan, Ying Wang, Wei Wang, Jinhan Xie, Shu Yang, Ziqian Zeng, and Xinyun Chen, 2022(16 May).
Heterogeneous logistic regression for estimation of subgroup effects on hypertension
Journal of Biopharmaceutical Statistics, 32(6), 969-985.(Multi-source Heterogeneous Data)
Xiaodong Yan#, Jinhan Xie, Wei Tu, Bei Jiang, Linglong Kong*, 2023.
Scalable inference for individual treatment effect
Statistics and its interface, forthcoming. (Multi-source Heterogeneous Data)
Wei Wang, Zhijie Xiao, Yanyan Ren, Xiaodong Yan*, 2023.
A Bi-integrative analysis of two-dimensional heterogeneous panel data models with group and cohort structure recovery
Economics Letters,230. (Multi-source Heterogeneous Data)
Hongni Wang#, Na Li#, Yanqiu Zhou#, Jingxin Yan, Bei Jiang, Linglong Kong*, Xiaodong Yan*, 2024.
Fast Fusion Clustering via Double Random Projection
Entropy, 26(5), 376. (Multi-source Heterogeneous Data)
Yuxi Guo#, Yuhang Li#, Yi Dong#
, Jingxin Yan#, Xiaodong Yan*, 2024.
Conformalized Fuzzy Subgroup Recovery for
Optimization-Free Heterogeneous Analysis
Statistics and its interfece, forthcoming. (Multi-source Heterogeneous Data)
Machine Learning
Na Zhang#, Jinhan Xie#, Xiaodong Yan#, Bei Jiang, Linglong Kong, Ting Li 2023
Renewable $\ell_1$-regularized linear support vector machine with high-dimensional streaming data
under review in Journal of Machine Learning Research (Online Learning)
Xiaodong Yan, Hongni Wang, Wei Wang, Jinhan Xie*,YanYan Ren*, Xinjun Wang*, 2021.
Optimal Model Averaging Forecasting in High-Dimensional Survival Analysis
International Journal of forecasting, 37(3),1147-1155. (Ensemble Learning)
Xianwen Ding, Jinhan Xie*, Xiaodong Yan*, 2021.
Model averaging for multiple quantile regression with covariates missing at random
Journal of Statistical Computation and Simulation, 91(11), 2249-2275. (Ensemble Learning)
Jinhan Xie, Xianwen Ding, Bei Jiang, Xiaodong Yan*, Linglong Kong*, 2023.
High-dimensional model averaging for quantile regression
Canadian Journal of Statistics, 52, 2, 2024, 618–635 (Ensemble Learning)
Weili Cheng，Xiaorui Li，Xiaoxia Li，
Xiaodong Yan*, 2023.
Model averaging for generalized linear models with missing at random covariates
Statistics,57,26-52(Ensemble Learning)
Huaijin Liang#, Jin Ma#, Wei Wang#*
Xiaodong Yan#, 2024.
Demystifying the Two-Armed
Futurity Bandit’s Unfairness and
Apparent Fairness.
Mathematics, 12, 1713. https://doi.org/10.3390/
math12111713 (Bandit Learning)
Zengjing Chen, Xiaodong Yan*, Donglin Zeng and Guodong Zhang, 2022.
More powerful similarity test using two-arm bandit sampling strategy
Journal of the American Statistical Association, under review (Reinforcement Learning)
Xiaodong Yan, Chen Zengjing, Jinhan Xie, Shuchang Liu, Linglong Kong, Bei Jiang, 2022
Differentially private online inference for streaming data
Statistica Sinica, under review (Online Learning)
Ke Sun, Yingnan Zhao, Yi Liu, Enze Shi, Yafei Wang, Aref Sadeghi, Xiaodong Yan, Bei Jiang, Linglong Kong, 2022
Interpreting Distributional Reinforcement Learning: Regularization and Optimization Perspectives
under review (Reinforcement Learning)
Artificial Intelligence Conference Paper
Hongni Wang, Junxi Zhang, Na Li, Bei Jiang, Linglong Kong, Xiaodong Yan*. 2025. (Top Conference)
Advancing Fairness in Precision Medicine: A Universal Framework for Optimal Treatment Estimation in Censored Data,
AISTATS. acceptance rate: 31.3% . (Fairness)
Shanshan Zhao, Wenhai Cui, Bei Jiang, Linglong Kong, Xiaodong Yan*. 2024. (Top Conference)
Responsible Bandit Learning via Privacy-Protected Mean-Volatility Utility,
Proceedings of the AAAI Conference on Artificial Intelligence, 38(19), 21815-21822. https://doi.org/10.1609/aaai.v38i19.30182, acceptance rate: 21.3% . (Reinforcement Learning)
Yangdi jiang, Yi Liu, Xiaodong Yan, Anne-Sophie Charest, Linglong Kong, Bei jiang*. 2024. (Top Conference)
Analysis of differentially private synthetic data:
a general measurement error approach
AAAI-23, acceptance rate: 21.3% . (Privacy Data)
Wenli Feng#, Xinlu Li#, Bei Jiang, Linglong Kong, Xiaodong Yan*. 2023. (Top Conference, Spotlight Paper)
P-learning for Two-sided Markets
KDD-23 Workshop on Decision Intelligence and Analytics for Online Marketplaces . (Two-sided Markets)
Hongni Wang, JingXin Yan, Xiaodong Yan*. 2023. (Top Conference)
Spearman Rank Correlation Screening for Ultrahigh-dimensional Censored Data
AAAI-23, acceptance rate: 19.6% . (High Dimensional Data)
Wenhai Cui, Xiaoting Ji, Linglong Kong Xiaodong Yan*. 2023. (Top Conference, Oral Presentation)
Opposite Online Learning via Sequentially Integrated Stochastic Gradient Descent Estimators, 817, 7270–7278
AAAI-23, acceptance rate: 19.6% , Oral Presentation rate: 10% . (Online Learning)
Statistical Learning for Some Applications (Biostatistics and Econometrics)
张琪,张娜,严晓东*, 2025.
大模型静默数据损坏的统计检验方法——基于均值波动统计量
《应用统计与数据科学》ASDS, 1(1): 40–44.(大模型)
Peiper Du#, Peihua Cao#, Xiaodong Yan#,..., Shu Yang, Xixi Feng. 2021.
A continuous age-specific standardizd mortality ratio for estimating the unascertained rates in the early epidemic of COVID-19 in different regions
Journal of Applied Statistics,50,2504-2517. (Biostatistics)
Shu Yang, Peipei Du, Daihai He, Yaolong Chen, Lidan Zhong, Xixi Feng, Xiaodong Yan*, Jiawei Luo*, 2022.
Propensity Score Analysis with Missing Data Using a Multi-Task Neural Networks
BMC Medical Research Methodology,23,41. (Biostatistics)
Rongmei Sun, Huimin Wang, Wei Wang, Qiang Qi, Dianjiang Yu, Xiaodong Yan*, 2022
Review of Crop Revenue Insurance in China and A New Estimation of Premium
invited revision submitted. (Econometrics)
Shuoxun Xu , Yang Xiao ,Wei Wang*, Xiaodong Yan*, 2022.
Integrative Analysis in Time-Phased Large Portfolios with Cohort and Sparsity Recovery
under review.(Econometrics)
Xixi Feng, Peipei Du, Guobao Li, Peihua Cao, Jiaohua Luo, Xiaodong Yan, Jiawei Luo, Daihai He, Lin Yang, Xiaohui Wang, Shu Yang, Yang Fu, Yaolong Chen,2022.
Epidemiological Characteristics of COVID-19 Deaths In China: An Analysis of Environmental Factors
under review. (Biostatistics)
陈增敬, 严晓东, 冯新伟, 2021.
金融科技中人工智能技术典型事实与核心规律
《中国科学基金》, 2021,35(03)，387-393.(Econometrics)
魏建, 王慧敏, 严晓东, 2023.
农业保险高质量发展与农民风险防范—基于费率区划的视角
《宏观质量研究》,2022,11(1):38-51,编号（2022.09.033 ）.(Econometrics)
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