ROP: Matrix Recovery via Rank-One Projections. - T. Tony Cai; Anru Zhang (CoRR, 2013)

Sharp RIP Bound for Sparse Signal and Low-Rank Matrix Recovery - T. Tony Cai; Anru Zhang (CoRR, 2013)

Compressed Sensing and Affine Rank Minimization Under Restricted Isometry. - T. Tony Cai; Anru Zhang (IEEE Trans. Signal Process., 2013)

Sparse Representation of a Polytope and Recovery of Sparse Signals and Low-Rank Matrices. - T. Tony Cai; Anru Zhang (IEEE Trans. Inf. Theory, 2014)

Cross: Efficient Low-rank Tensor Completion. - Anru Zhang (CoRR, 2016)

Inference for high-dimensional differential correlation matrices. - T. Tony Cai; Anru Zhang (J. Multivar. Anal., 2016)

Minimax rate-optimal estimation of high-dimensional covariance matrices with incomplete data. - T. Tony Cai; Anru Zhang (J. Multivar. Anal., 2016)

Guaranteed Tensor PCA with Optimality in Statistics and Computation. - Anru Zhang; Dong Xia (CoRR, 2017)

Estimation of Markov Chain via Rank-constrained Likelihood. - Xudong Li 004; Mengdi Wang; Anru Zhang (ICML, 2018)

State Compression of Markov Processes via Empirical Low-Rank Estimation. - Anru Zhang; Mengdi Wang (CoRR, 2018)

A Non-asymptotic, Sharp, and User-friendly Reverse Chernoff-Cramèr Bound. - Anru Zhang; Yuchen Zhou (CoRR, 2018)

Tensor SVD: Statistical and Computational Limits. - Anru Zhang; Dong Xia (IEEE Trans. Inf. Theory, 2018)

Open Problem: Average-Case Hardness of Hypergraphic Planted Clique Detection. - Yuetian Luo; Anru R. Zhang (COLT, 2020)

An Optimal Statistical and Computational Framework for Generalized Tensor Estimation. - Rungang Han; Rebecca Willett; Anru Zhang (CoRR, 2020)

Tensor Clustering with Planted Structures: Statistical Optimality and Computational Limits. - Yuetian Luo; Anru Zhang (CoRR, 2020)

A Schatten-q Matrix Perturbation Theory via Perturbation Projection Error Bound. - Yuetian Luo; Anru R. Zhang (CoRR, 2020)

Inference for Low-rank Tensors - No Need to Debias. - Dong Xia; Anru R. Zhang; Yuchen Zhou (CoRR, 2020)

ISLET: Fast and Optimal Low-Rank Tensor Regression via Importance Sketching. - Anru R. Zhang; Yuetian Luo; Garvesh Raskutti; Ming Yuan 001 (SIAM J. Math. Data Sci., 2020)

Sparse and Low-Rank Tensor Estimation via Cubic Sketchings. - Botao Hao; Anru Zhang; Guang Cheng 003 (IEEE Trans. Inf. Theory, 2020)

Spectral State Compression of Markov Processes. - Anru Zhang; Mengdi Wang (IEEE Trans. Inf. Theory, 2020)

Learning Good State and Action Representations via Tensor Decomposition. - Chengzhuo Ni; Anru R. Zhang; Yaqi Duan; Mengdi Wang (ISIT, 2021)

A Sharp Blockwise Tensor Perturbation Bound for Orthogonal Iteration. - Yuetian Luo; Garvesh Raskutti; Ming Yuan 001; Anru R. Zhang (J. Mach. Learn. Res., 2021)

Provable Second-Order Riemannian Gauss-Newton Method for Low-Rank Tensor Estimation ‖. - Yuetian Luo; Qin Ma 003; Chi Zhang 021; Anru R. Zhang (ICASSP, 2022)

Learning Polynomial Transformations. - Sitan Chen; Jerry Li 001; Yuanzhi Li; Anru R. Zhang (CoRR, 2022)

Tensor-on-Tensor Regression: Riemannian Optimization, Over-parameterization, Statistical-computational Gap, and Their Interplay. - Yuetian Luo; Anru R. Zhang (CoRR, 2022)

Self-supervised Denoising via Low-rank Tensor Approximated Convolutional Neural Network. - Chenyin Gao; Shu Yang; Anru R. Zhang (CoRR, 2022)

Learning Markov Models Via Low-Rank Optimization. - Ziwei Zhu; Xudong Li 004; Mengdi Wang; Anru Zhang (Oper. Res., 2022)

Sparse Group Lasso: Optimal Sample Complexity, Convergence Rate, and Statistical Inference. - T. Tony Cai; Anru R. Zhang; Yuchen Zhou (IEEE Trans. Inf. Theory, 2022)

Optimal High-Order Tensor SVD via Tensor-Train Orthogonal Iteration. - Yuchen Zhou; Anru R. Zhang; Lili Zheng; Yazhen Wang (IEEE Trans. Inf. Theory, 2022)

Statistical and Computational Limits for Tensor-on-Tensor Association Detection. - Ilias Diakonikolas; Daniel M. Kane; Yuetian Luo; Anru Zhang (COLT, 2023)

Sampling is as easy as learning the score: theory for diffusion models with minimal data assumptions. - Sitan Chen; Sinho Chewi; Jerry Li 001; Yuanzhi Li; Adil Salim; Anru Zhang (ICLR, 2023)

Phase transition for detecting a small community in a large network. - Jiashun Jin; Zheng Tracy Ke; Paxton Turner; Anru Zhang (ICLR, 2023)

Learning Polynomial Transformations via Generalized Tensor Decompositions. - Sitan Chen; Jerry Li 001; Yuanzhi Li; Anru R. Zhang (STOC, 2023)

Mode-wise Principal Subspace Pursuit and Matrix Spiked Covariance Model. - Runshi Tang; Ming Yuan 001; Anru R. Zhang (CoRR, 2023)

Fast and Reliable Generation of EHR Time Series via Diffusion Models. - Muhang Tian; Bernie Chen; Allan Guo; Shiyi Jiang; Anru R. Zhang (CoRR, 2023)

Low-rank Tensor Estimation via Riemannian Gauss-Newton: Statistical Optimality and Second-Order Convergence. - Yuetian Luo; Anru R. Zhang (J. Mach. Learn. Res., 2023)

Learning Good State and Action Representations for Markov Decision Process via Tensor Decomposition. - Chengzhuo Ni; Yaqi Duan; Munther A. Dahleh; Mengdi Wang; Anru R. Zhang (J. Mach. Learn. Res., 2023)

Tensor Decomposition Meets RKHS: Efficient Algorithms for Smooth and Misaligned Data. - Brett W. Larsen; Tamara G. Kolda; Anru R. Zhang; Alex H. Williams (CoRR, 2024)

Tensor Decomposition with Unaligned Observations. - Runshi Tang; Tamara G. Kolda; Anru R. Zhang (CoRR, 2024)

Federated PCA and Estimation for Spiked Covariance Matrices: Optimal Rates and Efficient Algorithm. - Jingyang Li; T. Tony Cai; Dong Xia; Anru R. Zhang (CoRR, 2024)

Recursive Importance Sketching for Rank Constrained Least Squares: Algorithms and High-Order Convergence. - Yuetian Luo; Wen Huang 001; Xudong Li 004; Anru Zhang (Oper. Res., 2024)

Reliable generation of privacy-preserving synthetic electronic health record time series via diffusion models. - Muhang Tian; Bernie Chen; Allan Guo; Shiyi Jiang; Anru R. Zhang (J. Am. Medical Informatics Assoc., 2024)

Soft phenotyping for sepsis via EHR time-aware soft clustering. - Shiyi Jiang; Xin Gai; Miriam M. Treggiari; William W. Stead; Yuankang Zhao; C. David Page; Anru R. Zhang (J. Biomed. Informatics, 2024)

On Geometric Connections of Embedded and Quotient Geometries in Riemannian Fixed-Rank Matrix Optimization. - Yuetian Luo; Xudong Li 004; Anru R. Zhang (Math. Oper. Res., 2024)

One-Dimensional Tensor Network Recovery. - Ziang Chen; Jianfeng Lu 001; Anru Zhang (SIAM J. Matrix Anal. Appl., 2024)

Cocaine Use Prediction With Tensor-Based Machine Learning on Multimodal MRI Connectome Data. - Anru R. Zhang; Ryan P. Bell; Chen An; Runshi Tang; Shana A. Hall; Cliburn Chan; Kareem Al-Khalil; Christina S. Meade (Neural Comput., 2024)

Nonconvex Factorization and Manifold Formulations Are Almost Equivalent in Low-Rank Matrix Optimization. - Yuetian Luo; Xudong Li 004; Anru R. Zhang (INFORMS J. Optim., 2025)

High-order Accurate Inference on Manifolds. - Chengzhu Huang; Anru R. Zhang (CoRR, 2025)

Revisit CP Tensor Decomposition: Statistical Optimality and Fast Convergence. - Runshi Tang; Julien Chhor; Olga Klopp; Anru R. Zhang (CoRR, 2025)