Selected Research in Methodology, Theory, and Computation
(group members are underlined and corresponding authors are denoted by *)
  • Bhattacharjee, S., Li, B. and Xue, L.* (2024)
    Nonlinear Global Fréchet Regression for Random Objects via Weak Conditional Expectation. (link, arXiv)
    The Annals of Statistics, in press.
  • Tao, J., Chen, Q.*, Snyder Jr., J. W., Kumar, A. S., Meisami, A. and Xue, L.* (2024)
    A Graphical Point Process Framework for Understanding Removal Effects in Multi-Touch Attribution. (arXiv, ssrn)
    Management Science, in press.
  • Zheng, Z., Gao, F., Xue, L.* and Yang, J.* (2024)
    Federated Q-Learning: Linear Regret Speedup with Low Communication Cost. (link, arXiv)
    Proceedings of The Twelfth International Conference on Learning Representations (ICLR), in press.
  • Chen, Q., Agarwal, A., Fong, D., DeSarbo, W. S. and Xue, L.* (2024)
    Model-Based Co-Clustering in Customer Targeting Utilizing Large-Scale Online Product Rating Networks. (link)
    Journal of Business & Economic Statistics, in press.
  • Zhang, Q., Xue, L.* and Li, B. (2023+)
    Dimension Reduction for Fréchet Regression. (link, arXiv)
    [Winner of 2023 ASA Nonparametric Statistics Best Student Paper Award]
    Journal of the American Statistical Association, in press.
  • Rios, N., Xue, L.* and Zhan, X. (2024)
    A Latent Variable Mixture Model for Composition-on-Composition Regression with Application to Chemical Recycling. (link)
    The Annals of Applied Statistics, 18: 3253-3273.
  • Zhang, Q., Li, B. and Xue, L.* (2024)
    Nonlinear Sufficient Dimension Reduction for Distribution-on-Distribution Regression. (link, arXiv)
    Journal of Multivariate Analysis, 202: 105302.
  • Liu, B., Zhang, Q. (co-first author), Xue, L.*, Song, P. X. K. and Kang, J. (2024)
    Robust High-Dimensional Regression with Coefficient Thresholding and its Application to Imaging Data Analysis. (link, arXiv) [Winner of 2019 ASA Statistics in Imaging Best Student Paper Award]
    Journal of the American Statistical Association, 119: 715-729.
  • Yu, X., Li, D. and Xue, L.* (2024)
    Fisher's Combined Probability Test for High-Dimensional Covariance Matrices. (link, arXiv)
    Journal of the American Statistical Association, 119: 511-524.
  • Tao, J., Li, B. and Xue, L.* (2024)
    An Additive Graphical Model for Discrete Data. (link, arXiv)
    Journal of the American Statistical Association, 119: 368-381.
  • Zheng, Z., Ma, S.* and Xue, L.* (2024)
    A New Inexact Proximal Linear Algorithm with Adaptive Stopping Criteria for Robust Phase Retrieval. (link, arXiv)
    IEEE Transactions on Signal Processing, 72: 1081-1093.
  • Yu, X., Yao, J. and Xue, L.* (2024)
    Power Enhancement for Testing Multi-Factor Asset Pricing Models via Fisher's Method. (link, ssrn)
    Journal of Econometrics, 239: 105458.
  • Yu, X., Li, D., Xue, L.* and Li, R. (2024)
    Power-Enhanced Simultaneous Test of High-Dimensional Mean Vectors and Covariance Matrices with Application to Gene-Set Testing. (link, arXiv)
    Journal of the American Statistical Association, 118: 2548-2561.
  • Li, D., Srinivasan, A. (co-first author), Chen, Q.* and Xue, L.* (2023)
    Robust Covariance Matrix Estimation for High-Dimensional Compositional Data with Application to Sales Data Analysis. (link)
    Journal of Business & Economic Statistics, 41: 1090-1100.
  • Li, D., Srinivasan, A. (co-first author), Xue, L.* and Zhan, X. (2023)
    Robust Shape Matrix Estimation for High-Dimensional Compositional Data with Application to Microbial Inter-Taxa Analysis. (link)
    Statistica Sinica, 33: 1577-1602.
  • Wang, Z., Liu, B. (co-first author), Chen, S., Ma, S., Xue, L.* and Zhao, H. (2022)
    A Manifold Proximal Linear Method for Sparse Spectral Clustering with Application to Single-Cell RNA Sequencing Data Analysis. (link, arXiv)
    INFORMS Journal on Optimization, 4: 200-214.
  • Wang, B., Ma, S. and Xue, L.. (2022)
    Riemannian Stochastic Proximal Gradient Methods for Nonsmooth Optimization over Stiefel Manifold. (link, arXiv)
    Journal of Machine Learning Research, 23: 1−33.
  • Yu, X., Yao, J. and Xue, L.* (2022)
    Nonparametric Estimation and Conformal Inference of the Sufficient Forecasting with a Diverging Number of Factors. (link) [Winner of 2018 ASA Business and Economic Statistics Distinguished Student Paper Award]
    Journal of Business & Economic Statistics, 40: 342-354.
  • Lee, K. H., Chen, Q.*, DeSarbo, W. S. and Xue, L.* (2022)
    Estimating Finite Mixtures of Ordinal Graphical Models. (link, arXiv)
    Psychometrika, 87: 83–106.
  • Luo, W., Xue, L.* (co-first author), Yao, J. and Yu, X.(2022)
    Inverse Moment Methods for Sufficient Forecasting using High-Dimensional Predictors. (link, arXiv, ssrn)
    Biometrika, 109: 473–487.
  • Srinivasan, A., Xue, L.* and Zhan, X. (2021)
    Compositional Knockoff Filter for FDR Control in Microbiome Regression Analysis. (link, bioRxiv)
    [Recognized as a top cited paper among work published in an issue between 1 January 2021 – 15 December 2022]
    Biometrics, 77: 984-995.
  • Ke, Z. T., Xue, L. and Yang, F. (2020)
    Diagonally-Dominant Principal Component Analysis. (link, arXiv)
    Journal of Computational and Graphical Statistics, 29: 592-607.
  • Chen, S., Ma, S., Xue, L. and Zou, H. (2020)
    An Alternating Manifold Proximal Gradient Method for Sparse PCA and Sparse CCA. (link, arXiv)
    INFORMS Journal on Optimization, 2: 192-208.
  • Du, K, Huddart, S. J., Xue, L. and Zhang, Y. (2020)
    Using a Hidden Markov Model to Measure Earnings Quality. (link, ssrn, earnings fidelity)
    Journal of Accounting & Economics, 69: 101281.
  • Lee, K. H., Xue, L.*, and Hunter, D. R. (2020)
    Model-Based Clustering of Time-Evolving Networks through Temporal ERGMs. (link, arXiv)
    [Winner of 2016 ASA Statistical Learning and Data Science Best Student Paper Award]
    Journal of Multivariate Analysis, 175: 104540.
  • Agarwal, A. and Xue, L.* (2020)
    Model-Based Clustering of Nonparametric Weighted Networks with Application to Water Pollution Analysis. (link)
    [Winner of 2018 ASA Risk Analysis Best Student Paper Award]
    Technometrics, 62: 161-172.
  • Zou, H. and Xue, L. (2018)
    A Selective Overview of Sparse Principal Component Analysis. (link)
    Proceedings of the IEEE, 106: 1311-1320.
  • Kim, B., Lee, K. H. (co-first author), Xue, L. and Niu, X. (2018)
    A Review of Dynamic Network Models with Latent Variables. (link)
    Statistics Surveys, 12: 105-135.
  • Li. D., Xue, L. (co-first author) and Zou, H. (2018)
    Applications of Peter Hall's Martingale Limit Theory to Estimating and Testing High Dimensional Covariance Matrices. (link)
    Statistica Sinica, 28: 2657-2670.
  • Lee, K. H. and Xue, L.* (2018)
    Nonparametric Finite Mixture of Gaussian Graphical Models. (link, arXiv)
    [Winner of 2016 ICSA Distinguished Student Paper Award]
    Technometrics, 60: 511-521.
  • Fan, J., Xue, L.* and Yao, J. (2017)
    Sufficient Forecasting Using Factor Models. (link, arXiv, ssrn)
    Jounral of Econometrics, 201: 292-306.
  • Fan, J., Xue, L. and Zou, H. (2016)
    Multi-Task Quantile Regression Under the Transnormal Model. (link, pdf)
    Journal of the American Statistical Association, 111: 1726-1735.
  • Fan, J., Xue, L. and Zou, H. (2014)
    Strong Oracle Optimality of Folded Concave Penalized Estimation. (link, arXiv)
    The Annals of Statistics, 42: 819-849.
  • Xue, L. and Zou, H. (2014).
    Rank-based Tapering Estimation of Bandable Correlation Matrices. (link)
    Statistica Sinica, 24: 83-100.
  • Ma, S., Xue, L. and Zou, H. (2013)
    Alternating Direction Methods for Latent Variable Gaussian Graphical Model Selection. (link, arXiv)
    Neural Computation, 25: 2172-2198.
  • Xue, L. and Zou, H. (2013).
    Minimax Optimal Estimation of General Bandable Covariance Matrices. (link)
    Journal of Multivariate Analysis, 116: 45-51.
  • Xue, L., Zou, H. and Cai, T. (2012).
    Nonconcave Penalized Composite Conditional Likelihood Estimation of Sparse Ising Models. (link, arXiv)
    The Annals of Statistics, 40(3): 1403-1429.
  • Xue, L. and Zou, H. (2012).
    Regularized Rank-Based Estimation of High-Dimensional Nonparanormal Graphical Models. (link, arXiv)
    The Annals of Statistics, 40(5): 2541-2571.
  • Xue, L., Ma, S. and Zou, H. (2012).
    Positive-Definite L1-Penalized Estimation of Large Covariance Matrices. (link, arXiv)
    Journal of the American Statistical Association, 107: 1480-1491.
  • Xue, L. and Zou, H. (2011).
    Sure Independence Screening and Compressed Random Sensing. (link)
    Biometrika, 98(2): 371-380.
Selected Research in Applications
(group members are underlined and corresponding authors are denoted by *)
  • Din, M., Paul, S., Ullah, S., Yang, H., Xu, R. G., Abidin, N. A. Z., Sun, A., Chen, Y. C., Gao, R., Chowdhury, B., Zhou, F., Rogers, S., Miller, M., Biswas, A., Hu, L., Fan, Z., Zaher, Fan, J., Chen, Z., C., Berman, M., Xue, L., Ju, L., and Chen, Y. (2024)
    Multi-Parametric Thrombus Profiling Microfluidics Detects Intensified Biomechanical Thrombogenesis Associated with Hypertension and Aging. (link)
    Nature Communications. 15: 9067.
  • Shaheen, S., Wen, T., Zheng, Z., Xue, L., Baka, J. and Brantley, S. L. (2024).
    Wastewaters Co-Produced with Shale Gas Drive Slight Regional Salinization of Groundwater. (link)
    Environmental Science & Technology. 58: 17862-17873.
  • Agarwal, A., Wen, T., Chen, A., Zhang, A. Y., Niu, X., Zhan, X., Xue, L.* and Brantley, S. L. (2020).
    Assessing Contamination of Stream Networks Near Shale Gas Development Using a New Geospatial Tool. (link)
    Environmental Science & Technology, 54: 8632–8639.
  • Chen, Y., Ju, L., Zhou, F., Liao, J., Xue, L., Su, Q., Yuan, Y., Lu, H., Jackson, S. and Zhu C. (2019).
    An Integrin αIIbβ3 Intermediate Affinity State Mediates Biomechanical Platelet Aggregation. (link)
    [Featured in Georgia Tech News, University of Sydney News, Heart Research Institute News, Penn State News, EurekAlert! Science News, Scimex, ScienceDaily, Medical Xpress, and BioPortfolio]
    Nature Materials, 18, 760–769.
  • Wen, T., Agarwal, A. (co-first author), Xue, L.*, Chen, A., Herman, A., Li, Z. and Brantley, S. L. (2019).
    Assessing Changes in Groundwater Chemistry in Landscapes with More Than 100 Years of Oil and Gas Development. (link)
    Environmental Science: Processes & Impacts, 21, 384-396.
  • Lin, N., Jing, R., Wang, Y., Yonekura, E., Fan, F. and Xue, L. (2017).
    A Statistical Investigation of the Dependence of Tropical Cyclone Intensity Change on the Surrounding Environment. (link)
    Monthly Weather Review, 145, 2813-2831.
  • Ju, L., Chen, Y., Xue, L., Du, X. and Zhu C. (2016).
    Cooperative Unfolding of Distinctive Mechanoreceptor Domains Transduces Force into Signals. (link)
    [Featured in NSF Science360, Georgia Tech News and Penn State News]
    eLife, e15447.
Whitepaper
  • Rridgeway, G, Rosenberger, J & Xue, L. (2020)
    A Call for Statisticians to Engage in Gun Violence Research. (pdf)
    Statistics Serving Society, National Institute of Statistical Sciences.
  • Rudin, C, Dunson, D, Irizarry, R, Ji, H, Laber, E, Leek, J, McCormick, T, Rose, S, Schafer, C, van der Laan, M, Wasserman, L & Xue, L. (2014)
    Discovery with Data: Leveraging Statistics with Computer Science to Transform Science and Society. (pdf, website)
    [Featured in Amstat News, Consortium of Social Science Associations, Statistics Views, and The American Statistician]
    Science Policy and Advocacy, American Statistical Association.