My research is supported in part by NSF CAREER-1944904, NSF DMS-1811868, and NIH R01 GM131399.
Slides of recent work
Discussions
Preprints awaiting publication :-)
Publications
Inference for low-rank tensors -- No need to debias (with Dong Xia and Yuchen Zhou), The Annals of Statistics , to appear.
On the non-asymptotic concentration of heteroskedastic Wishart-type matrix (with Tony Cai and Rungang Han), Electronic Journal of Probability , to appear.
Optimal high-order tensor SVD via tensor-train orthogonal iteration (with Yuchen Zhou, Lili Zheng, and Yazhen Wang), IEEE Transactions on Information Theory , to appear. [R Package ]
Sparse Group Lasso: Optimal Sample Complexity, Convergence Rate, and Statistical Inference (with Tony Cai and Yuchen Zhou), IEEE Transactions on Information Theory , to appear.
A Schatten-q low-rank matrix perturbation analysis via perturbation projection error bound (with Yuetian Luo and Rungang Han), Linear Algebra and Its Applications , 630, 225-240, 2021.
Tensor clustering with planted structures: Statistical optimality and computational limits (with Yuetian Luo), The Annals of Statistics , to appear, 2021.
An optimal statistical and computational framework for generalized tensor estimation (with Rungang Han and Rebecca Willett), The Annals of Statistics , to appear, 2021.
A sharp blockwise tensor perturbation bound for orthogonal iteration (with Yuetian Luo, Garvesh Raskutti, and Ming Yuan), Journal of Machine Learning Research , 22, 1-48, 2021.
Heteroskedastic PCA: Algorithm, optimality, and applications (with Tony Cai and Yihong Wu), The Annals of Statistics , to appear.
High-dimensional log-error-in-variable regression with applications to microbial compositional data analysis (with Pixu Shi and Yuchen Zhou), Biometrika , to appear, 2021.
(This paper received Biometrics Early-Stage Investigator Award by the Biometrics Section of the American Statistical Association, 2019)
Learning good state and action representations via tractable tensor decomposition (with Chengzhuo Ni, Yaqi Duan and Mengdi Wang), International Symposium on Information Theory (ISIT) , 2021.
ISLET: fast and optimal low-rank tensor regression via importance sketchings (with Yuetian Luo, Garvesh Raskutti, and Ming Yuan), SIAM Journal on Mathematics of Data Science , 2, 444-479, 2020. [R package ]
Learning Markov models via low-rank optimization (with Ziwei Zhu, Xudong Li and Mengdi Wang), Operations Research , to appear.
Nonparametric covariance estimation for mixed longitudinal studies, with applications in midlife women's health (with Kehui Chen), Statistica Sinica , 32, 345-365, 2022.
Open problem: Average-case hardness of hypergraphic planted clique detection (with Yuetian Luo), Conference on Learning Theory (COLT) , 125, 3852-3856, 2020. [talk and slides]
On the non-asymptotic and sharp tail bounds of random variables (with Yuchen Zhou), Stat , 9, e314, 2020.
Sparse and low-rank tensor estimation via cubic sketchings (with Botao Hao and Guang Cheng), IEEE Transactions on Information Theory , 66, 9, 2020.
A short version published in Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics (AISTATS) , 2020.
Multi-sample estimation of bacterial composition matrix in metagenomics data (with Yuanpei Cao and Hongzhe Li), Biometrika , 107, 75-92, 2020.
Spectral state compression of Markov processes (with Mengdi Wang), IEEE Transactions on Information Theory , 66, 3202-3231, 2020.
Cross: Efficient low-rank tensor completion (single author), The Annals of Statistics , 47, 936-964, 2019. [R package ]
Optimal sparse singular value decomposition for high-dimensional high-order data (with Rungang Han), Journal of American Statistical Association , 114, 1708-1725, 2019. [R package ]
Semi-supervised inference: General theory and estimation of means (with Lawrence Brown and Tony Cai), The Annals of Statistics , 47, 2538-2566, 2019.
Tensor SVD: Statistical and computational limits (with Dong Xia), IEEE Transactions on Information Theory , 64, 1-28, 2018. [An R implementation ]
Sequential rerandomization (with Quan Zhou, Philip Ernst, Kari Lock Morgan, and Donald Rubin), Biometrika , 105, 745-752, 2018.
Rate-optimal perturbation bounds for singular subspaces with applications to high-Dimensional statistics (with Tony Cai), The Annals of Statistics , 46, 60-89, 2018.
Estimation of Markov chain via rank-constrained likelihood (with Mengdi Wang and Xudong Li), International Conference on Machine Learning (ICML) , PMLR 80:3033-3042, 2018.
Structured matrix completion with applications in genomic data integration (with Tianxi Cai and Tony Cai), Journal of American Statistical Association , 111, 621-633, 2016. [R package ]
Regression Analysis for Microbiome Compositional Data (with Pixu Shi and Hongzhe Li), The Annals of Applied Statistics , 10, 1019-1040, 2016. [Matlab package ]
Instrumental variables estimation with some invalid instruments and its application to Mendelian randomization (with Hyunseung Kang, Tony Cai and Dylan Small), Journal of American Statistical Association , 111, 132-144, 2016. [R Package ]
Minimax rate-optimal estimation of high-dimensional covariance matrices with incomplete data (with Tony Cai), Journal of Multivariate Analysis , 150, 55-74, 2016.
Inference for high-dimensional differential correlation matrices (with Tony Cai), Journal of Multivariate Analysis , 143, 107-126, 2016.
ROP: matrix recovery via rank-one projections (with Tony Cai), The Annals of Statistics , 43, 102-138, 2015.
Sparse representation of a polytope and recovery of sparse signals and low-rank matrices (with Tony Cai), IEEE Transactions on Information Theory , 60, 122-132, 2014.
Sharp RIP bound for sparse signal and low-rank matrix recovery (with Tony Cai), Applied and Computational Harmonic Analysis , 35, 74-93, 2013.
Compressed sensing and affine rank minimization under restricted isometry (with Tony Cai), IEEE Transactions on Signal Processing , 61, 3279-3290, 2013.
Collaborative Research
Ventriculomegaly and postoperative intraventricular blood predict cerebrospinal fluid diversion following posterior fossa tumor resection (Park, C., Liu, B., Harward, S., Zhang, A. R. et al.), Journal of Neurosurgery: Pediatrics , to appear.
Denoising Atomic Resolution 4D Scanning Transmission Electron Microscopy Data with Tensor Singular Value Decomposition (with Chenyu Zhang, Rungang Han, and Paul Voyles), Ultramicroscopy , 219, 113123, 2020.
LTMG: a novel statistical modeling of transcriptional expression states in single-cell RNA-Seq data (Wan, C. et al.) Nucleic Acids Research , 2019.
Other Manuscripts