Publications

*Corresponding Author. ^†All authors contribute equally to this work. Authors are listed alphabetically by last name. ^#Co-first author.

• Y. Chao, X. C. Xia*, and W. Zhong^†. Communication-Efficient Pilot Estimation for Non-Randomly Distributed Data in Diverging Dimensions[J]. Journal of Computational and Graphical Statistics, 35(1): 155–172, 2026. DOI: https://doi.org/10.1080/10618600.2025.2513964.
• Z. Q. Qin, Y. Chao^#, and X. J. Ma*. Distributed Quadratic Interpolation Estimation for Large-Scale Quantile Regression[J]. Journal of Parallel and Distributed Computing. 210:105214, 2025. DOI: https://doi.org/10.1016/j.jpdc.2025.105214.
• Y. Z. Zhao, X. J. Ma, and Y. Chao*. Spatial Lag Quantile Regression in Compositional Data[J]. Communications in Statistics - Simulation and Computation, 54(12): 5123–5138, 2025. DOI: https://doi.org/10.1080/03610918.2024.2436011.
• X .F. Wu, Y. Chao^#, S. Tang, R. M. Liang, and Z. M. Zhang*. Feature Splitting Parallel Algorithm for Dantzig Selectors[J]. Statistics and Computing, 35:116, 2025. DOI: https://doi.org/10.1007/s11222-025-10658-y.
• Z. D. Zhang, Y. Chao, and X. J. Ma*. Robust Distributed Estimation for Modal Regression under Least Squares Approximation[J]. ACM Transactions on Knowledge Discovery from Data, 19(6): 1-21, 2025. DOI: https://doi.org/10.1145/3742477.
• Y. Chao, L. Huang, and X. J. Ma*^†. Distributed Optimization for Penalized Regression in Massive Compositional Data[J]. Applied Mathematical Modelling, 141: 115950, 2025. DOI:https://doi.org/10.1016/j.apm.2025.115950.
• Y. Chao, X. J. Ma*, and B. Y. Zhu. Distributed Optimal Subsampling for Quantile Regression with Massive Data[J]. Journal of Statistical Planning and Inference, 233: 106186, 2024. DOI: https://doi.org/10.1016/j.jspi.2024.106186.
• J. R. Chen, X. J. Ma, and Y. Chao*. Testing Independence for Multivariate Time Series via Auto Multivariate Distance Covariance[J]. Communications in Statistics-Theory and Methods, 54(5), 1397–1409, 2024. DOI: https://doi.org/10.1080/03610926.2024.2338418.
• Y. Chao, L. Huang, X. J. Ma*, and J. J. Sun. Optimal Subsampling for Modal Regression in Massive Data[J]. Metrika, 87: 379–409, 2024. DOI: https://doi.org/10.1007/s00184-023-00916-2.
• L. Shen, Y. Chao, and X. J. Ma*. Distributed Quantile Regression in Decentralized Optimization[J]. Information Sciences, 643: 119259, 2023. DOI: https://doi.org/10.1016/j.ins.2023.119259.
• Y. Chao, X. J. Ma, Y. G. Li, and L. Huang*. A Penalized Estimation for the Cox Model with Ordinal Multinomial Covariates[J]. Journal of Statistical Computation and Simulation, 92(6): 1194-1223, 2022. DOI: https://doi.org/10.1080/00949655.2021.1989692.
• 晁越, 谭雨昕, 许丹, 黄磊*. 关于含顺序类别解释变量的Logistic回归模型研究[J]. 统计与信息论坛, 36(03): 20-31, 2021.
• L. Huang, W. Q. Hang*, and Y. Chao. High-dimensional Regression with Ordered Multiple Categorical Predictors[J]. Statistics in Medicine, 39(3): 294-309, 2020. DOI: https://doi.org/10.1002/sim.8400.

Papers Under Revision and Review

• L. Huang, Y. Chao^#, X. Y. Li, C. Y. Wu*. Multi-Source Risk Assessment on Distributed Systems via Pilot Sampling-Fused Survival Modeling. Submitted.
• M. Y. Wang, Y. Chao^#, W. Zhong*. Modal Tensor Regression: Robust Learning of Representative Structure in Skewed Tensor Data. Submitted.
• Y. Du, Y. Chao*. Moment-Free Robust Distributed Reduced-Rank Regression in High Dimensions. Submitted.
• C. Y. Wu, W. Zhong, Y. Chao, Q. X. Zhong*. FedCox: Federated Locally-adaptive Cox Proportional Hazards Models. Submitted.
• Y. Chao, W. F. Liu*. Rao-Blackwellized Optimal Subsampling with Multi-Resolution Partitioning in Large-Scale Softmax Regression. Submitted.

Working Papers

• Tensor Elastic Screening and Localized Alignment on a Distributed System.
• Modifier-Splitting Coefficient Trees for Varying Coefficients.
• Distributed Subsampling for Massive Logistic Partially Linear Models under Auxiliary Summary Statistics.
• Optimal Decorrelated score Pairwise Subsampling for Diverging-dimensional Convoluted Rank Rgeression via Randomized Incomplete U-Statistics.
• Optimal Decorrelated score Subsampling for High-Dimensional Modal Regression with Massive Data.
• Residual Importance Weighted Transfer Learning in Sparse Robust Convoluted Reduced-Rank Multivariate Regression.
• Robust Angle-Based Transfer Learning for High-Dimensional Modal Spatial Autoregressive Models.