My research is supported in part by NSF CAREER-1944904, NSF DMS-1811868, and NIH R01 GM131399.
Slides of recent work
Preprints awaiting publication :-)
- 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.
- 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.