Weidong liu (刘卫东) - 上海交通大学

个人简介

2011-- Professor, School of Mathematical Sciences and Institute of Natural Sciences, Shanghai Jiao Tong University 2009--2011 Postdoctoral Fellow, Department of Statistics, The Wharton School,University of Pennsylvania 2008--2009 Postdoctoral Fellow, Department of Mathematics, Hong Kong University of Science and Technology 2003--2008 Ph.D. in Mathematics, Zhejiang University, P.R. China Honors and Awards National Excellent Doctoral Dissertation Award from China, 2010 New World Mathematics Awards, Silver Award for the Ph.D Thesis, 2010. Former Phd students, Postdoc Wang Xiaozhou, assistant professor, East China Normal University Zhu Yunlong, assistant professor, Shanghai University Luo Shan (postdoc), associate professor, Shanghai Jiao Tong University Master students 20+students in IT (Alibaba, Tencent, Ctrip,ByteDance, ...)

研究领域

Modern statistics Machine learning Probability Optimization

近期论文

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Machine learning and Optimization Multi-consensus decentralized primal-dual fixed point algorithm for distributed learning. Technical report, 2022.[pdf] Fast Decentralized Median Value Estimation. Technical report, 2022. Accelerated online averaging over networks.Technical report, 2022. Fast and Robust Sparsity Learning over Networks: A Decentralized Surrogate Median Regression Approach. IEEE Transactions on Signal Processing, to appear. 2022.[pdf] Distributed Estimation on Semi-Supervised Generalized Linear Model. Technical report, 2022. Majority Vote for Distributed Differentially Private Sign Selection. Technical report, 2022. https://arxiv.org/abs/2209.04419[pdf] Byzantine-Tolerant Distributed Multiclass Sparse Linear Discriminant Analysis, The 38th Conference on Uncertainty in Artificial Intelligence (UAI 2022). DEMO: A Flexible Deartifacting Module for Compressed Sensing MRI, IEEE Journal of Selected Topics in Signal Processing, to appear. 2022.[pdf] Byzantine-robust distributed sparse learning for M-estimation. Machine Learning, to appear. 2021. [pdf] Variance reduced median-of means estimator for Byzantine-robust distributed inference. Journal of Machine Learning Research, 1-67. 2021.[pdf] First-order Newton-type estimator for distributed estimation and inference. Journal of the American Statistical Association, to appear. 2021.[pdf] Robust reduced rank regression in a distributed setting. Science China- Mathematics, to appear. 2021 [pdf] Distributed high-dimensional regression under a quantile loss function. Journal of Machine Learning Research, 182, 1-43. 2020[pdf] Bayesian decision process for budget-efficient crowdsourced clustering. International Joint Conferences on Artificial Intelligence, 2020.[pdf] Median matrix completion: from embarrassment to optimality. Proceedings of the 37 th International Conference on Machine Learning, Online, PMLR 119, 2020. [pdf] Distributed inference for linear support vector machine. Journal of Machine Learning Research, 20(113), 1-41. 2019 [pdf] Quantile regression under memory constraint. Annals of Statistics, 47 (6), 3244-3273. 2019 [pdf] Graphical models/linear regression/t tests with false discovery rate control and application False discovery control for pairwise comparisons - an asymptotic solution to Williams, Jones and Tukey's conjecture. Technical report. 2018 [pdf] Graph estimation for matrix-variate Gaussian data. Statistica Sinica, 29, 479-504. 2019 Structural similarity and difference testing on multiple sparse Gaussian graphical models. Annals of Statistics, 45, 2680-2707. 2017 [matlab code] Large-Scale Multiple Testing of Correlations. Journal of the American Statistical Association, 111, 229-240. 2016 [pdf] Incorporation of Sparsity Information in Large-scale Multiple Two-sample t Tests. Technical report. 2014 [pdf] [matlab code] [matlab code] Hypothesis Testing for High-dimensional Regression Models. Technical report. 2014 [pdf] Phase Transition and Regularized Bootstrap in Large-scale t-tests with False Discovery Rate Control. Annals of Statistics, 42, 2003-2025. 2014 [matlab code] Gaussian Graphical Model Estimation with False Discovery Rate Control. Annals of Statistics, 41, 2948-2978. 2013 [matlab code] Phenome-wide association study of autoantibodies to citrullinated and non-citrullinated epitopes in rheumatoid arthritis. Arthritis & Rheumatology, 69, 742-749. 2017 The (inverse) covariance matrix estimation and classification Estimating Sparse Precision Matrix: Optimal Rates of Convergence and Adaptive Estimation. Annals of Statistics, 44, 455-488. 2016 Joint Estimation of Multiple High-dimensional Precision Matrices. Statistica Sinica, 26, 445-464. 2016 Fast and adaptive sparse precision matrix estimation in high dimensions. Journal of Multivariate Analysis, 135, 153-162. 2015 Covariate Adjusted Precision Matrix Estimation with an Application in Genetical Genomics. Biometrika, 100: 139-156. 2013 [pdf] A Direct Estimation Approach to Sparse Linear Discriminant Analysis. Journal of the American Statistical Association. 106: 1566-1577. 2011 [matlab code] A constrained L1 minimization approachto sparse precision matrix estimation. Journal of the American Statistical Association. 106: 594-607. 2011 Adaptive thresholding for sparse covariance matrix estimation. Journal of the American Statistical Association. 106: 672-684.(with correction in the proof) 2011 [correction] [matlab code] Various maximum type statistics with applications to global testing and inference Simultaneous nonparametric regression analysis of sparse longitudinal data. Bernoulli, 24, 3013-3038. 2018 Testing independence with high-dimensional correlated samples. Annals of Statistics, 46, 866-894. 2018 Simultaneous confidence bands in nonlinear regression models with nonstationarity. Statistica Sinica, 27, 1385-1400. 2017 Two-Sample Test of High Dimensional Means under Dependency. Journal of the Royal Statistical Society - Series B, 76, 349-372. 2014 Two-Sample Covariance Matrix Testing And Support Recovery in High-dimensional and Sparse Settings. Journal of the American Statistical Association, 108: 265-277. 2013 [pdf] [Supplement] Simultaneous nonparametric inference of time series. The Annals of Statistics. 38: 2388-2421. 2010 Asymptotics of spectral density estimates. Econometric Theory. 26: 1218-1245. 2010 Necessary and sufficient conditions for the asymptotic distribution of the largest entry of a sample correlation matrix. Probability Theory and Related Fields. 148: 5-35. 2010 On maxima of periodograms of stationary processes, The Annals of Statistics, 37:2676-2695. 2009 The asymptotic distribution and Berry-Esseen bound of a new test for independence in high dimension with an application to stochastic optimization, The Annals of Applied Probability, 18: 2337-2366. 2008 Invariance principle under dependence Gaussian approximations for weighted empirical processes under dependence. Technical report. 2018 [pdf] Komlos-Major-Tusnady approximation under dependence. Annals of Probability, 42, 794-817. 2014 Uniform approximation to local time with applications in non-linear cointegrating regression. Published in a book by Wang, Q. 2014[pdf] On non-stationary threshold autoregressive models. Bernoulli. 17: 969-986. 2011 Strong approximation for a class of stationary processes, Stochastic Processes and their Applications,119: 249-280. 2009 [pdf] Self-normalized limiting theorem A Cramer moderate deviation theorem for Hotelling T2-statistic with applications to global tests. Annals of Statistics, 41: 296-322. 2013 Self-normalized Cram\'{e}r type large deviations for the maximum of sums of independent random variables. Bernoulli, 19, 1006-1027. 2013 [pdf] Cramer type moderate deviation for the maximum of the periodogram with application to simultaneous tests. The Annals of Statistics. 38: 1913-1935. 2010 [pdf]