Xingcai Zhou
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Selected publications

Technical report

  • Bidirectional Efficient Non-Convex Adaptive Federated Learning
    X.C. Zhou, G. Yang & L.L. Kong

  • Functional Linear Operator Quantile Regression for Sparse Longitudinal Data
    X.C. Zhou, T.Y. Lai & L.L. Kong

  • Communication-efficient and privacy-preserving multi-site learning and score test for ordered response logit model based on electronic health record data for heart failure
    X.C. Zhou, & H.Y. Chen

2025

  • Distribution-on-scalar Single-index Quantile Regression Model for Handling Tumor Heterogeneity
    X.C. Zhou, S. Ding, J. Wang, R. Liu, L.L. Kong & C. Huang
    Techonometrics, 2025+, https://doi.org/10.1080/00401706.2024.2441686

  • Communication-efficient non-convex distributed learning with error feedback for uplink and downlink
    X.C. Zhou, Le Chang & Jinde Cao
    IEEE Transactions on Neural Networks and Learning Systems, 2025+, https://ieeexplore.ieee.org/document/10327766

  • 广义线性模型分布式学习的无损Score检验----多站点心力衰竭EHRs数据分析
    周兴才, 陈慧莹 & 林金官
    数理统计与管理, 2025+ (accepted)

2024

  • Confounder adjustment in single index function-on-scalar regression model
    S.X. Ding, X.C. Zhou, J.G Lin, R.J. Liu & C. Huang
    Electronic Journal of Statistics, 18(2) 5679 - 5714, 2024.

  • Shape Mediation Analysis in Alzheimer’s Disease Studies
    X.C. Zhou, M. Yeon, J. Wang, S. Ding, K. Lei, Y.Y. Zhao, R.J. Liu, C. Huang & ADNI
    Statistics in Medicine, 43:5698–5710, 2024.

  • Efficient distributed transfer learning for large-scale Gaussian graphic models
    X.C. Zhou, H.T. Zheng, H.R. Zhang & C. Huang
    Stat, 13: e70004, 2024.

  • Communication-efficient Byzantine-robust distributed inference with error feedback: a trade-off between compression and adversary
    X.C. Zhou, G. Yang, L. Chang & S.G. Lv
    Information Sciences, 678: 121010, 2024.

  • More Communication-efficient distributed sparse learning
    X.C. Zhou & G. Yang
    Information Sciences, 668: 120523, 2024.

  • Empirical likelihood M-estimation for the varying-coefficient model with functional response
    X.C. Zhou, D.H. Kong, M. Pietrosanu, L.L. Kong & R. Karunamuni
    Scandinavian Journal of Statistics, 51:1357–1387, 2024.

  • Federated Learning with Communication-Efficiency and Privacy-Preserving Counteracting Heterogeneity
    X.C. Zhou & G. Yang
    Information Sciences, 661: 120167, 2024.

  • Distributed bootstrap simultaneous inference for high-dimensional quantile regression
    X.C. Zhou Z.Y. Jing & C. Huang
    Mathematics, 12(5), 735, 2024.

2023

  • Functional Response Quantile Regression Model
    X.C. Zhou, D.H. Kong, A.B. Kashlak, L.L. Kong, R. Karunamuni & H.T. Zhu
    Statistica Sinica, 33, 2643-2667, 2023.

  • Communication-efficient Byzantine-robust distributed learning with statistical guarantee
    X.C. Zhou, L. Chang, P.F. Xu & S.G. Lv
    Pattern Recognition, 137: 109312, 2023.

2022

  • Reproducing kernel-based functional linear expectile regression
    M.C. Liu, P. Matthew, P. Liu, B. Jiang, X.C. Zhou & L.L. Kong
    The Canadian Journal of Statistics, 50(1):241-266, 2022.

  • Uniform convergence rates for wavelet curve estimation in sup-norm loss
    X.C. Zhou
    Journal of Computational and Applied Mathematics, 400, 113752, 2022.

  • Panel semiparametric quantile regression neural network for electricity consumption forecasting
    X.C. Zhou, J.Y. Wang, H.X. Wang & J.G. Lin
    Ecological Informatics, 67, 101489, 2022.

  • Discussion of: ‘A review of distributed statistical inference’
    S.G. Lv & X.C. Zhou
    Statistical Theory and Related Fields, 6(2): 105-107, 2022.

  • ADMM-Based Differential Privacy Learning for Penalized Quantile Regression on Distributed Functional Data
    X.C. Zhou & Y. Xiang
    Mathematics, 10(16), 2954, 2022.

  • Communication-efficient distributed learning for high-dimensional support vector machine
    X.C. Zhou & H. shen
    Mathematics, 10(7), 1029, 2022.

2021

  • Robust wavelet-based estimation for varying coefficient dynamic models under long-dependent structures
    X.C. Zhou & S.G. Lv
    Analysis and Applications, 19(6): 1033-1057, 2021

  • The asymptotic properties of scad penalized generalized linear models with adaptive designs
    Q.B. Gao, C.H. Zhu, X.L. Du, X.C. Zhou & D.X. Yin
    Journal of Systems Science & Complexity, 34: 759–773, 2021

  • Panel quantile regression neural network for electricity consumption forecasting in China: a new framework
    X.C. Zhou & J.Y. Wang
    Energy Sources, Part B: Economics, Planning, and Policy, 16(5): 420-442, 2021

2008-2020

  • A General Framework for Quantile Estimation with Incomplete Data
    P.S. Han，L.L. Kong，J.W. Zhao & X.C. Zhou
    Journal of the Royal Statistical Society: Series B (Statistical Methodology), 81(2): 305-333, 2019 (Top)

  • Berry-Esseen bounds for wavelet estimator in time-varying model with censored dependent data
    X.C. Zhou, B.B. Ni, H.X. Wang & X.F. Huang
    Mathematica Slovaca, 69(5), 1213-1232, 2019

  • Wavelet estimation in time-varying coefficient models
    X.C. Zhou, B.B. Ni & C.H. Zhu
    Lithuanian Mathematical Journal, 59(2): 276-293, 2019

  • Wavelet-based LASSO in functional linear quantile regression
    Y.F. Wang, L.L. Kong, B. Jiang, X.C. Zhou, S.M. Yu, L. Zhang & G. Heo
    Journal of Statistical Computation and Simulation, 89(6): 1111-1130, 2019

  • Asymptotics of a wavelet estimator in the nonparametric regression model with repeated measurements under a NA error process
    X.C. Zhou & J.G. Lin
    Revista de la Real Academia de Ciencias Exactas, Fisicas y Naturales. Serie A--Matematicas, 109:153-168, 2015

  • Empirical likelihood inference in mixture of semiparametric varying coefficient models for longitudinal data with nonignorable dropout
    X.C. Zhou & J.G. Lin
    Statistics, 48: 668-684, 2014

  • Empirical likelihood for varying-coefficient semiparametric mixed-effects error-in-variables models with longitudinal data
    X.C. Zhou & J.G. Lin
    Statistical Methods and Applications, 23: 51-69, 2014

  • Asymptotic properties of wavelet estimators in semiparametric regression models under dependent errors
    X.C. Zhou & J.G. Lin
    Journal of Multivariate Analysis, 122: 251-270, 2013

  • Empirical likelihood inference in mixtures of semiparametric varying coefficient EV models for longitudinal data with nonignorable Dropout
    X.C. Zhou & J.G. Lin
    Journal of the Korean Statistical Society, 42: 215-225, 2013

  • Semiparametric regression estimation for longitudinal data in models with martingale difference error’s structure
    X.C. Zhou & J.G. Lin
    Statistics, 47(3): 521-534, 2013

  • On complete convergence for strong mixing sequence
    X.C. Zhou & J.G. Lin
    Stochastics, 85(2): 262-271, 2013

  • On moments of the maximum of partial sums of moving average processes under dependence assumptions
    X.C. Zhou & J.G. Lin
    Acta Mathematicae Applicatae Sinica, English Series, 27: 691-696, 2011

  • Complete moment convergence of moving average processes under ρ-mixing assumption
    X.C. Zhou & J.G. Lin
    Mathematica Slovaca, 61: 979-992, 2011

  • Moment consistency of estimators in partially linear models under NA samples
    X.C. Zhou, X.S. Liu & S.H. Hu
    Metrika, 72(2): 415-432, 2010

  • The Monte Carlo EM method for estimating multivariate tobit latent variable models
    X.C. Zhou & X.S. Liu
    Jouranl of Statistical Computation & Simulation, 79(9): 1095-1107, 2009

  • The EM algorithm for the extended finite mixture of factor analyzers model
    X.C. Zhou & X.S. Liu
    Computational Statistics and Data Analysis, 52(8): 3939-3953, 2008

  • The Monte Carlo EM method for estimating multinomial probit latent variable models
    X.C. Zhou & X.S. Liu
    Computational Statistics, 23(2): 277-289, 2008