Publications

I would like to gratefully acknowledge the research support as the Principal Investigator (PI) by the National Science Foundation grants (2014-present, including a CAREER Award), a Simons Fellowship, UIUC Research Board Awards (including an Arnold O. Beckman Award), Center for Advanced Study, and a start-up grant from UIUC.

Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

(* indicates students advised)

Mean-field nonparametric estimation of interacting particle systems.
Rentian Yao*, Xiaohui Chen, Yun Yang.
Conference on Learning Theory (COLT), 2022.

Sketch-and-lift: scalable subsampled semidefinite program for K-means clustering.
Yubo Zhuang*, Xiaohui Chen, Yun Yang.
Artificial Intelligence and Statistics Conference (AISTATS), 2022. [Code]

Central limit theorems for high dimensional dependent data.
Jinyuan Chang, Xiaohui Chen, Mingcong Wu.
First version: April 2021.

Maximum likelihood estimation of potential energy in interacting particle systems from single-trajectory data.
Xiaohui Chen.
Electronic Communications in Probability, 2021, Vol. 26, paper no. 45, 1-13. DOI

Geometric flows.
Xiaohui Chen.

First version: July 2020. This version: December 2020.
(Lecture notes under construction, comments are welcome.)

Scenario analysis of non-pharmaceutical interventions on global COVID-19 transmissions.
Xiaohui Chen, Ziyi Qiu.
Covid Economics: Vetted and Real-Time Papers, Centre for Economic Policy Research (CEPR), 46-67, Issue 7, 20 April 2020. (Preliminary version, VoxEU column)

Stratified incomplete local simplex tests for curvature of nonparametric multiple regression.
Yanglei Song*, Xiaohui Chen, Kengo Kato.
Bernoulli, accepted, 2022. [Code]

A note on Stein equation for weighted sums of independent $\chi^{2}$ distributions.
Xiaohui Chen, Partha Dey.
First version: February 2020.

Robust inference for partially observed functional response data.
Yeonjoo Park, Xiaohui Chen, Douglas G. Simpson.
Statistica Sinica, accepted, 2021. DOI

Cutoff for exact recovery of Gaussian mixture models.
Xiaohui Chen, Yun Yang.
IEEE Transactions on Information Theory, 2021, 67(6), 4223-4238. DOI

Estimation of dynamic networks for high-dimensional nonstationary time series.
Mengyu Xu, Xiaohui Chen, Wei Biao Wu.
Entropy, 22(1):55, 2020. DOI

A robust bootstrap change point test for high-dimensional location parameter.
Mengjia Yu*, Xiaohui Chen.
Electronic Journal of Statistics, 16(1), 1096-1152, 2022. DOI

Diffusion K-means clustering on manifolds: provable exact recovery via semidefinite relaxations.
Xiaohui Chen, Yun Yang.
Applied and Computational Harmonic Analysis, 2021, Vol 52, 303-347. DOI

Approximating high-dimensional infinite-order U-statistics: statistical and computational guarantees.
Yanglei Song*, Xiaohui Chen, Kengo Kato.
Electronic Journal of Statistics, 2019, 13(2), 4794-4848. DOI

U-statistics.
Xiaohui Chen.
Wiley StatsRef: Statistics Reference Online, 2019. DOI

Hanson-Wright inequality in Hilbert spaces with application to K-means clustering for non-Euclidean data.
Xiaohui Chen, Yun Yang.
Bernoulli, 2021, 27(1), 586-614. DOI

Randomized incomplete U-statistics in high dimensions.
Xiaohui Chen, Kengo Kato.
Annals of Statistics, 2019, 47(6), 3127-3156. DOI

Finite sample change point inference and identification for high-dimensional mean vectors.
Mengjia Yu*Xiaohui Chen.
Journal of the Royal Statistical Society, Series B (Statistical Methodology), 2021, 83(2), 247-270. DOI

Jackknife multiplier bootstrap: finite sample approximations to the U-process supremum with applications.
Xiaohui Chen, Kengo Kato.
Probability Theory and Related Fields, 2020, 176(3), 1097-1163. DOI

Gaussian and bootstrap approximations for high-dimensional U-statistics and their applications.
Xiaohui Chen.
Annals of Statistics, 2018, 46(2), 642-678. DOI
(This paper supersedes the arXiv preprint “Gaussian approximation for the sup-norm of high-dimensional matrix-variate U-statistics and its applications.“)

Inference of high-dimensional linear models with time-varying coefficients.
Xiaohui Chen, Yifeng He*.
Statistica Sinica, 2018, 28(1), 255-276. DOI

Sparse transition matrix estimation for high-dimensional and locally stationary vector autoregressive models.
Xin Ding*, Ziyi Qiu, Xiaohui Chen.
Electronic Journal of Statistics, 2017, 11(2),3871-3902. DOI [Code]

Regularized estimation of linear functionals of precision matrices for high-dimensional time series.
Xiaohui Chen, Mengyu Xu, Wei Biao Wu.
IEEE Transactions on Signal Processing, 2016, 64(24), 6459-6470. DOI

Discussion of “High-dimensional autocovariance matrices and optimal linear prediction.”
Xiaohui Chen.
Electronic Journal of Statistics, 2015, Vol. 9, 801-810. DOI

A note on moment inequality for quadratic forms.
Xiaohui Chen.
Statistics and Probability Letters, 2014, Vol. 92, 83-88. DOI

A genetically-informed, group fMRI connectivity modeling approach: application to Schizophrenia.
Aiping Liu, Xiaohui Chen, Z. Jane Wang, Qi Xu, Silke Appel-Cresswell, Martin J. McKeown.
IEEE Transactions on Biomedical Engineering, 2014, 61(3), 946-956. DOI

Covariance and precision matrix estimation for high-dimensional time series.
Xiaohui Chen, Mengyu Xu, Wei Biao Wu.
Annals of Statistics, 2013, 41(6), 2994-3021. DOISupplementary file.

Efficient minimax estimation of a class of high-dimensional sparse precision matrices.
Xiaohui Chen, Young-Heon Kim, Z. Jane Wang.
IEEE Transactions on Signal Processing, 
2012, 60(6), 2899-2912. DOI

Shrinkage-to-tapering estimation of large covariance matrices.
Xiaohui Chen
, Z. Jane Wang, Martin J. McKeown.
IEEE Transactions on Signal Processing, 
2012, 60(11), 5640-5656DOI

A two-graph guided multi-task Lasso approach for eQTL mapping.
Xiaohui Chen
, Xinghua Shi, Xing Xu, Zhiyong Wang, Ryan E. Mills, Charles Lee, Jinbo Xu.
Artificial Intelligence and Statistics Conference (AISTATS), 2012. [Code]

Large covariance matrices estimation: bridging shrinkage and tapering approaches.
Xiaohui Chen
, Z. Jane Wang, Martin J. McKeown.
International Conference on Acoustics, Speech, and Signal Processing (ICASSP),
2012. DOI

A Bayesian Lasso via reversible-jump MCMC.
Xiaohui Chen, Z. Jane Wang, Martin J. McKeown.
Signal Processing
, 2011, 91(8), 1920-1932. DOI

Asymptotic analysis of robust LASSOs in the presence of noise with large variance.
Xiaohui Chen, Z. Jane Wang, Martin J. McKeown.
IEEE Transactions on Information Theory, 2010, 56(10), 5131-5149. DOI

fMRI group studies of brain connectivity via a group robust LASSO.
Xiaohui Chen
, Z. Jane Wang, Martin J. McKeown.
International Conference on Image Processing (ICIP), 2010. DOI

Asymptotic analysis of the Huberized LASSO estimator.
Xiaohui Chen, Z. Jane Wang, Martin J. McKeown.
International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2010. DOI

A sparse unified structural equation modeling approach for brain connectivity analysis.
Xiaohui Chen, Z. Jane Wang, Martin J. McKeown.
International Conference on Bioinformatics and Biomedical Engineering (iCBBE), 2009. pdf

An MM-based optimization algorithm for sparse linear modeling on microarray data analysis.
Xiaohui Chen, Raphael Gottardo.
International Conference on Bioinformatics and Biomedical Engineering (iCBBE), 2009. DOI

BNArray: an R package for constructing gene regulatory networks from microarray data by using Bayesian network.
Xiaohui Chen, Ming Chen, Kaida Ning.
Bioinformatics, 2006, 22(23), 2952-2954. DOI