Anru R. Zhang

发表

A Sharp Blockwise Tensor Perturbation Bound for Orthogonal Iteration pdf

Garvesh Raskutti, Yuetian Luo, Ming Yuan, 2020, ArXiv.

Inference for Low-rank Tensors - No Need to Debias pdf

Anru R. Zhang, Dong Xia, Yuchen Zhou, 2020, ArXiv.

Recursive Importance Sketching for Rank Constrained Least Squares: Algorithms and High-order Convergence pdf

Wen Huang, Xudong Li, Yuetian Luo, 2020, ArXiv.

Optimal High-order Tensor SVD via Tensor-Train Orthogonal Iteration pdf

Yazhen Wang, Yuchen Zhou, Anru R. Zhang, 2020, ArXiv.

Tensor Clustering with Planted Structures: Statistical Optimality and Computational Limits pdf

Yuetian Luo, Anru R. Zhang, Yuetian Luo, 2020, The Annals of Statistics.

A Schatten-q Matrix Perturbation Theory via Perturbation Projection Error Bound pdf

Yuetian Luo, Anru R. Zhang, 2020, ArXiv.

Open Problem: Average-Case Hardness of Hypergraphic Planted Clique Detection pdf

Yuetian Luo, Anru R. Zhang, Yuetian Luo, 2020, COLT 2020.

Low-rank Tensor Estimation via Riemannian Gauss-Newton: Statistical Optimality and Second-Order Convergence pdf

Yuetian Luo, Anru R. Zhang, 2021, ArXiv.

ROP: Matrix Recovery via Rank-One Projections pdf

Anru Zhang, Anru R. Zhang, T. Tony Cai, 2013, ArXiv.

Regression Analysis for Microbiome Compositional Data

Anru R. Zhang, Hongzhe Li, Pixu Shi, 2016, 1603.00974.

On the non-asymptotic concentration of heteroskedastic Wishart-type matrix

Anru R. Zhang, T. Cai, Rungang Han, 2020, Electronic Journal of Probability.

A Sharp Blockwise Tensor Perturbation Bound for Orthogonal Iteration

Anru R. Zhang, M. Yuan, G. Raskutti, 2020, J. Mach. Learn. Res..

High-dimensional Statistical Inference: from Vector to Matrix

Anru R. Zhang, 2015 .

Functional data approaches for mixed longitudinal studies, with applications in midlife women's health

Anru R. Zhang, Kehui Chen, 2017 .

An Optimal Statistical and Computational Framework for Generalized Tensor Estimation

Anru R. Zhang, R. Willett, Rungang Han, 2020, The Annals of Statistics.

Optimal Sparse Singular Value Decomposition for High-Dimensional High-Order Data

Anru R. Zhang, Rungang Han, 2018, Journal of the American Statistical Association.

Denoising atomic resolution 4D scanning transmission electron microscopy data with tensor singular value decomposition.

Anru R. Zhang, P. Voyles, Rungang Han, 2020, Ultramicroscopy.

LTMG: a novel statistical modeling of transcriptional expression states in single-cell RNA-Seq data

Yu Zhang, Wennan Chang, Changlin Wan, 2019, Nucleic acids research.

LTMG: A novel statistical modeling of transcriptional expression states in single-cell RNA-Seq data

Anru R. Zhang, Qin Ma, M. Fishel, 2018 .

Semi-supervised inference: General theory and estimation of means

Anru Zhang, Anru R. Zhang, T. Tony Cai, 2016, The Annals of Statistics.

An Optimal Statistical and Computational Framework for Generalized Tensor Estimation pdf

Rungang Han, Rebecca Willett, Anru Zhang, 2020, The Annals of Statistics.

ROP: MATRIX RECOVERY VIA RANK-ONE PROJECTIONS1 BY T. TONY CAI

Anru R. Zhang, 2014 .

On the non‐asymptotic and sharp lower tail bounds of random variables

Anru Zhang, Yuchen Zhou, Anru R. Zhang, 2018, Stat.

Nonparametric covariance estimation for mixed longitudinal studies, with applications in midlife women's health

Anru R. Zhang, Kehui Chen, 2017, 1711.00101.

ICTD: Inference of cell types and deconvolution -- a next generation deconvolution method for accurate assess cell population and activities in tumor microenvironment

Anru R. Zhang, Xinna Zhang, Xiongbin Lu, 2018, bioRxiv.

Tensor-on-Tensor Regression: Riemannian Optimization, Over-parameterization, Statistical-computational Gap, and Their Interplay

Anru R. Zhang, Yuetian Luo, 2022, ArXiv.

One-dimensional Tensor Network Recovery

Anru R. Zhang, Jianfeng Lu, Ziang Chen, 2022, ArXiv.

Tensor-on-Tensor Regression: Riemannian Optimization, Over-parameterization, Statistical-computational Gap, and Their Interplay

Anru R. Zhang, Yuetian Luo, 2022, ArXiv.

Sampling is as easy as learning the score: theory for diffusion models with minimal data assumptions

Anru R. Zhang, Yuanzhi Li, Jungshian Li, 2022, ArXiv.

Tensor-on-Tensor Regression: Riemannian Optimization, Over-parameterization, Statistical-computational Gap, and Their Interplay

Anru R. Zhang, Yuetian Luo, 2022, ArXiv.

Low-rank Tensor Estimation via Riemannian Gauss-Newton: Statistical Optimality and Second-Order Convergence

Anru R. Zhang, Yuetian Luo, 2021, ArXiv.

Nonconvex Factorization and Manifold Formulations are Almost Equivalent in Low-rank Matrix Optimization

Anru R. Zhang, Yuetian Luo, Xudong Li, 2021, ArXiv.

Recursive Importance Sketching for Rank Constrained Least Squares: Algorithms and High-order Convergence

Anru R. Zhang, Wen Huang, Yuetian Luo, 2020, Operations Research.

ROP: MATRIX RECOVERY VIA RANK-ONE PROJECTIONS 1

Anru R. Zhang, 2015 .

Guaranteed Functional Tensor Singular Value Decomposition*

Anru R. Zhang, Pixu Shi, Rungang Han, 2021, Journal of the American Statistical Association.

Rate-Optimal Perturbation Bounds for Singular Subspaces with Applications to High-Dimensional Statistics

Anru R. Zhang, T. Cai, 2016, 1605.00353.

Sparse Group Lasso: Optimal Sample Complexity, Convergence Rate, and Statistical Inference

Anru R. Zhang, T. Cai, Yuchen Zhou, 2019, IEEE Transactions on Information Theory.

Instrumental Variables Estimation With Some Invalid Instruments and its Application to Mendelian Randomization

Dylan S. Small, Anru R. Zhang, Anru Zhang, 2014, 1401.5755.

On the non‐asymptotic and sharp lower tail bounds of random variables

Anru R. Zhang, Yuchen Zhou, 2018, Stat.

On the non-asymptotic concentration of heteroskedastic Wishart-type matrix

Anru R. Zhang, T. Cai, Rungang Han, 2020, Electronic Journal of Probability.

Multisample estimation of bacterial composition matrices in metagenomics data

Anru R. Zhang, Hongzhe Li, Yuanpei Cao, 2020 .

Heteroskedastic PCA: Algorithm, optimality, and applications

Anru R. Zhang, T. Cai, Yihong Wu, 2018, The Annals of Statistics.

A Schatten-q Matrix Perturbation Theory via Perturbation Projection Error Bound

Anru R. Zhang, Yuetian Luo, 2020, ArXiv.

Inference for high-dimensional differential correlation matrices

Anru Zhang, Anru R. Zhang, T. Tony Cai, 2014, J. Multivar. Anal..

Inference for Low-rank Tensors - No Need to Debias

Anru R. Zhang, Dong Xia, Yuchen Zhou, 2020, The Annals of Statistics.

Tensor SVD: Statistical and Computational Limits

Anru R. Zhang, Anru Zhang, Dong Xia, 2017, IEEE Transactions on Information Theory.

ICTD: A semi-supervised cell type identification and deconvolution method for multi-omics data

Chi Zhang, Szu-wei Tu, Wennan Chang, 2018 .

Structured Matrix Completion with Applications to Genomic Data Integration

Anru Zhang, Tianxi Cai, Anru R. Zhang, 2015, Journal of the American Statistical Association.

Microbial Composition Estimation from Sparse Count Data

Anru R. Zhang, Hongzhe Li, Yuanpei Cao, 2017 .

Multi-sample Estimation of Bacterial Composition Matrix in Metagenomics Data

Anru R. Zhang, Hongzhe Li, Yuanpei Cao, 2017, 1706.02380.

On Geometric Connections of Embedded and Quotient Geometries in Riemannian Fixed-rank Matrix Optimization pdf

Yuetian Luo, Anru R. Zhang, Xudong Li, 2021, ArXiv.

ISLET: Fast and Optimal Low-rank Tensor Regression via Importance Sketching

Anru R. Zhang, M. Yuan, G. Raskutti, 2019, SIAM J. Math. Data Sci..

Sampling is as easy as learning the score: theory for diffusion models with minimal data assumptions

Anru R. Zhang, Yuanzhi Li, Jungshian Li, 2022, ICLR.

Sharp RIP bound for sparse signal and low-rank matrix recovery pdf

Anru Zhang, Anru R. Zhang, T. Tony Cai, 2013 .

Learning Polynomial Transformations via Generalized Tensor Decompositions

Anru R. Zhang, Yuanzhi Li, Jungshian Li, 2023, STOC.

Sparse Representation of a Polytope and Recovery of Sparse Signals and Low-Rank Matrices

Anru Zhang, Anru R. Zhang, T. Tony Cai, 2013, IEEE Transactions on Information Theory.

Exact clustering in tensor block model: Statistical optimality and computational limit

Anru R. Zhang, Rungang Han, Yuetian Luo, 2020, Journal of the Royal Statistical Society: Series B (Statistical Methodology).

Core shrinkage covariance estimation for matrix-variate data

Anru R. Zhang, P. Hoff, A. Mccormack, 2022, Journal of the Royal Statistical Society Series B: Statistical Methodology.

On Geometric Connections of Embedded and Quotient Geometries in Riemannian Fixed-rank Matrix Optimization

Anru R. Zhang, Yuetian Luo, Xudong Li, 2021, Mathematics of Operations Research.

A Schatten-q low-rank matrix perturbation analysis via perturbation projection error bound

Rungang Han, Yuetian Luo, Anru R. Zhang, 2020, 2008.01312.

Sparse and Low-Rank Tensor Estimation via Cubic Sketchings

Anru Zhang, Anru R. Zhang, Guang Cheng, 2018, IEEE Transactions on Information Theory.

High-dimensional Statistical Inference: from Vector to Matrix

Anru R. Zhang, 2015 .

Learning Good State and Action Representations via Tensor Decomposition

Anru R. Zhang, Mengdi Wang, Yaqi Duan, 2021, International Symposium on Information Theory.

Learning Good State and Action Representations for Markov Decision Process via Tensor Decomposition

Anru R. Zhang, Mengdi Wang, M. Dahleh, 2023, Journal of machine learning research.

Compressed Sensing and Affine Rank Minimization Under Restricted Isometry

Anru Zhang, Anru R. Zhang, T. Tony Cai, 2013, IEEE Transactions on Signal Processing.

Optimal High-Order Tensor SVD via Tensor-Train Orthogonal Iteration

Anru R. Zhang, Yazhen Wang, Yuchen Zhou, 2020, IEEE Transactions on Information Theory.

Learning Markov Models Via Low-Rank Optimization

Mengdi Wang, Anru R. Zhang, Anru Zhang, 2019, Oper. Res..

Spectral State Compression of Markov Processes

Anru Zhang, Mengdi Wang, Anru R. Zhang, 2018, IEEE Transactions on Information Theory.

Cross: Efficient Low-rank Tensor Completion pdf

Anru Zhang, Anru R. Zhang, 2016, The Annals of Statistics.

Minimax rate-optimal estimation of high-dimensional covariance matrices with incomplete data

Anru Zhang, Anru R. Zhang, T. Tony Cai, 2016, J. Multivar. Anal..

High-dimensional Log-Error-in-Variable Regression with Applications to Microbial Compositional Data Analysis

Anru R. Zhang, Anru Zhang, Yuchen Zhou, 2018, 1811.11709.

A semi-supervised approach for cell phenotypic and functional estimation in tissue microenvironment

Chi Zhang, Szu-wei Tu, Wennan Chang, 2019 .

Mode-wise Principal Subspace Pursuit and Matrix Spiked Covariance Model

Anru R. Zhang, M. Yuan, Runshi Tang, 2023, ArXiv.

Low-rank Tensor Estimation via Riemannian Gauss-Newton: Statistical Optimality and Second-Order Convergence

Anru R. Zhang, Yuetian Luo, 2021, ArXiv.

Instrumental Variables Estimation With Some Invalid Instruments and its Application to Mendelian Randomization

Dylan S. Small, Anru R. Zhang, T. T. Cai, 2014, 1401.5755.

Estimation of Markov Chain via Rank-constrained Likelihood pdf

Anru Zhang, Mengdi Wang, Xudong Li, 2018, ICML.

Supplementary Materials for “ Estimation of Markov Chain via Rank-Constrained Likelihood ”

Anru R. Zhang, Mengdi Wang, Xudong Li, 2018 .

Sharp RIP Bound for Sparse Signal and Low-Rank Matrix Recovery

Anru R. Zhang, Tommaso Cai, 2013, ArXiv.

Optimal Sparse Singular Value Decomposition for High-Dimensional High-Order Data

Anru R. Zhang, Rungang Han, 2018, Journal of the American Statistical Association.

Tensor Clustering with Planted Structures: Statistical Optimality and Computational Limits

Anru R. Zhang, Yuetian Luo, 2020, The Annals of Statistics.