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An Optimal Statistical and Computational Framework for Generalized
  Tensor Estimation
v1v2 (latest)

An Optimal Statistical and Computational Framework for Generalized Tensor Estimation

Annals of Statistics (Ann. Stat.), 2020
26 February 2020
Rungang Han
Rebecca Willett
Anru R. Zhang
ArXiv (abs)PDFHTML

Papers citing "An Optimal Statistical and Computational Framework for Generalized Tensor Estimation"

50 / 50 papers shown
Near-Efficient and Non-Asymptotic Multiway Inference
Near-Efficient and Non-Asymptotic Multiway Inference
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Arvind Prasadan
Carlos Llosa-Vite
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Daniel M. Dunlavy
153
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07 Nov 2025
Guaranteed Noisy CP Tensor Recovery via Riemannian Optimization on the Segre Manifold
Guaranteed Noisy CP Tensor Recovery via Riemannian Optimization on the Segre Manifold
Ke Xu
Yuefeng Han
131
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0
01 Oct 2025
Optimal Bias-variance Tradeoff in Matrix and Tensor Estimation
Optimal Bias-variance Tradeoff in Matrix and Tensor Estimation
Shivam Kumar
Haotian Xu
Carlos Misael Madrid Padilla
Y. Khoo
Oscar Hernan Madrid Padilla
Daren Wang
238
1
0
22 Sep 2025
A Scalable Factorization Approach for High-Order Structured Tensor Recovery
A Scalable Factorization Approach for High-Order Structured Tensor Recovery
Zhen Qin
Michael B. Wakin
Zhihui Zhu
229
5
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19 Jun 2025
Accelerating Large-Scale Regularized High-Order Tensor Recovery
Accelerating Large-Scale Regularized High-Order Tensor Recovery
Wenjin Qin
Hailin Wang
Jingyao Hou
Jianjun Wang
337
1
0
11 Jun 2025
Federated Low-Rank Tensor Estimation for Multimodal Image Reconstruction
Federated Low-Rank Tensor Estimation for Multimodal Image Reconstruction
Anh Van Nguyen
Diego Klabjan
Minseok Ryu
Kibaek Kim
Zichao Di
177
0
0
04 Feb 2025
Robust Low-rank Tensor Train Recovery
Robust Low-rank Tensor Train RecoveryIEEE Transactions on Signal Processing (IEEE TSP), 2024
Zhen Qin
Zhihui Zhu
341
3
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19 Oct 2024
Computational and Statistical Guarantees for Tensor-on-Tensor Regression with Tensor Train Decomposition
Computational and Statistical Guarantees for Tensor-on-Tensor Regression with Tensor Train DecompositionIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024
Zhen Qin
Zhihui Zhu
646
9
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10 Jun 2024
Tensor Methods in High Dimensional Data Analysis: Opportunities and
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Tensor Methods in High Dimensional Data Analysis: Opportunities and Challenges
Arnab Auddy
Dong Xia
Ming Yuan
AI4CE
319
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28 May 2024
On the Complexity of First-Order Methods in Stochastic Bilevel
  Optimization
On the Complexity of First-Order Methods in Stochastic Bilevel OptimizationInternational Conference on Machine Learning (ICML), 2024
Jeongyeol Kwon
Dohyun Kwon
Hanbaek Lyu
340
15
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11 Feb 2024
Guaranteed Nonconvex Factorization Approach for Tensor Train Recovery
Guaranteed Nonconvex Factorization Approach for Tensor Train Recovery
Zhen Qin
M. Wakin
Zhihui Zhu
486
15
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05 Jan 2024
Sharp Analysis of Power Iteration for Tensor PCA
Sharp Analysis of Power Iteration for Tensor PCAJournal of machine learning research (JMLR), 2024
Yuchen Wu
Kangjie Zhou
519
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02 Jan 2024
Convergence Analysis for Learning Orthonormal Deep Linear Neural
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Convergence Analysis for Learning Orthonormal Deep Linear Neural NetworksIEEE Signal Processing Letters (IEEE SPL), 2023
Zhen Qin
Xuwei Tan
Zhihui Zhu
360
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24 Nov 2023
Improving tensor regression by optimal model averaging
Improving tensor regression by optimal model averagingJournal of the American Statistical Association (JASA), 2023
Qiushi Bu
Hua Liang
Xinyu Zhang
Jiahui Zou
184
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22 Nov 2023
Provably Accelerating Ill-Conditioned Low-rank Estimation via Scaled
  Gradient Descent, Even with Overparameterization
Provably Accelerating Ill-Conditioned Low-rank Estimation via Scaled Gradient Descent, Even with Overparameterization
Cong Ma
Xingyu Xu
Tian Tong
Yuejie Chi
407
12
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09 Oct 2023
Mode-wise Principal Subspace Pursuit and Matrix Spiked Covariance Model
Mode-wise Principal Subspace Pursuit and Matrix Spiked Covariance ModelJournal of The Royal Statistical Society Series B-statistical Methodology (JRSSB), 2023
Runshi Tang
M. Yuan
Anru R. Zhang
288
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02 Jul 2023
On High-dimensional and Low-rank Tensor Bandits
On High-dimensional and Low-rank Tensor BanditsInternational Symposium on Information Theory (ISIT), 2023
Chengshuai Shi
Cong Shen
N. Sidiropoulos
238
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06 May 2023
Statistical and computational rates in high rank tensor estimation
Statistical and computational rates in high rank tensor estimation
Chanwoo Lee
Miaoyan Wang
400
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08 Apr 2023
Deflated HeteroPCA: Overcoming the curse of ill-conditioning in
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Deflated HeteroPCA: Overcoming the curse of ill-conditioning in heteroskedastic PCAAnnals of Statistics (Ann. Stat.), 2023
Yuchen Zhou
Yuxin Chen
371
10
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10 Mar 2023
On the Multiway Principal Component Analysis
On the Multiway Principal Component Analysis
Jialin Ouyang
Ming Yuan
317
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14 Feb 2023
Efficient Estimation for Longitudinal Networks via Adaptive Merging
Efficient Estimation for Longitudinal Networks via Adaptive MergingJournal of the American Statistical Association (JASA), 2022
H. Zhang
Junhui Wang
436
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15 Nov 2022
Group SLOPE Penalized Low-Rank Tensor Regression
Group SLOPE Penalized Low-Rank Tensor RegressionJournal of machine learning research (JMLR), 2022
Yang Chen
Ziyan Luo
241
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24 Aug 2022
Optimal Clustering by Lloyd Algorithm for Low-Rank Mixture Model
Optimal Clustering by Lloyd Algorithm for Low-Rank Mixture Model
Zhongyuan Lyu
Dong Xia
494
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Fast and Provable Tensor Robust Principal Component Analysis via Scaled
  Gradient Descent
Fast and Provable Tensor Robust Principal Component Analysis via Scaled Gradient DescentInformation and Inference A Journal of the IMA (JIII), 2022
Harry Dong
Tian Tong
Cong Ma
Yuejie Chi
317
19
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18 Jun 2022
Tensor-on-Tensor Regression: Riemannian Optimization,
  Over-parameterization, Statistical-computational Gap, and Their Interplay
Tensor-on-Tensor Regression: Riemannian Optimization, Over-parameterization, Statistical-computational Gap, and Their InterplayAnnals of Statistics (Ann. Stat.), 2022
Yuetian Luo
Anru R. Zhang
367
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Multivariate Analysis for Multiple Network Data via Semi-Symmetric
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Multivariate Analysis for Multiple Network Data via Semi-Symmetric Tensor PCA
Michael Weylandt
George Michailidis
376
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09 Feb 2022
Multiway Spherical Clustering via Degree-Corrected Tensor Block Models
Multiway Spherical Clustering via Degree-Corrected Tensor Block ModelsIEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2022
Jiaxin Hu
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Long Random Matrices and Tensor Unfolding
Long Random Matrices and Tensor Unfolding
Gerard Ben Arous
Daniel Zhengyu Huang
Jiaoyang Huang
379
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Provable Tensor-Train Format Tensor Completion by Riemannian
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Provable Tensor-Train Format Tensor Completion by Riemannian OptimizationJournal of machine learning research (JMLR), 2021
Jian-Feng Cai
Jingyang Li
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333
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Tensor Principal Component Analysis in High Dimensional CP Models
Tensor Principal Component Analysis in High Dimensional CP ModelsIEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2021
Yuefeng Han
Cun-Hui Zhang
436
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Guaranteed Functional Tensor Singular Value Decomposition
Guaranteed Functional Tensor Singular Value DecompositionJournal of the American Statistical Association (JASA), 2021
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Pixu Shi
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Latent Space Model for Higher-order Networks and Generalized Tensor
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Latent Space Model for Higher-order Networks and Generalized Tensor DecompositionJournal of Computational And Graphical Statistics (JCGS), 2021
Zhongyuan Lyu
Dong Xia
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Learning Good State and Action Representations via Tensor Decomposition
Learning Good State and Action Representations via Tensor DecompositionJournal of machine learning research (JMLR), 2021
Chengzhuo Ni
Yaqi Duan
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Mengdi Wang
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Scaling and Scalability: Provable Nonconvex Low-Rank Tensor Estimation
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Scaling and Scalability: Provable Nonconvex Low-Rank Tensor Estimation from Incomplete MeasurementsJournal of machine learning research (JMLR), 2021
Tian Tong
Cong Ma
Ashley Prater-Bennette
Erin E. Tripp
Yuejie Chi
444
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Low-rank Tensor Estimation via Riemannian Gauss-Newton: Statistical
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Low-rank Tensor Estimation via Riemannian Gauss-Newton: Statistical Optimality and Second-Order ConvergenceJournal of machine learning research (JMLR), 2021
Yuetian Luo
Anru R. Zhang
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Generalized Low-rank plus Sparse Tensor Estimation by Fast Riemannian
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Generalized Low-rank plus Sparse Tensor Estimation by Fast Riemannian OptimizationJournal of the American Statistical Association (JASA), 2021
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Dong Xia
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Beyond the Signs: Nonparametric Tensor Completion via Sign Series
Beyond the Signs: Nonparametric Tensor Completion via Sign SeriesNeural Information Processing Systems (NeurIPS), 2021
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High-Dimensional Low-Rank Tensor Autoregressive Time Series Modeling
High-Dimensional Low-Rank Tensor Autoregressive Time Series ModelingJournal of Econometrics (JE), 2021
Di Wang
Yao Zheng
Guodong Li
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Inference for Low-rank Tensors -- No Need to Debias
Inference for Low-rank Tensors -- No Need to DebiasAnnals of Statistics (Ann. Stat.), 2020
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Yuchen Zhou
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Exact Clustering in Tensor Block Model: Statistical Optimality and
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Spectral Methods for Data Science: A Statistical Perspective
Spectral Methods for Data Science: A Statistical Perspective
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Low-rank matrix estimation in multi-response regression with measurement
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Xin Li
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Statistical and computational thresholds for the planted kkk-densest sub-hypergraph problemInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2020
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Wojtek Szpankowski
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A Sharp Blockwise Tensor Perturbation Bound for Orthogonal Iteration
A Sharp Blockwise Tensor Perturbation Bound for Orthogonal Iteration
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Garvesh Raskutti
M. Yuan
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372
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Stochastic Low-rank Tensor Bandits for Multi-dimensional Online Decision
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Stochastic Low-rank Tensor Bandits for Multi-dimensional Online Decision MakingJournal of the American Statistical Association (JASA), 2020
Jie Zhou
Botao Hao
Zheng Wen
Jingfei Zhang
W. Sun
369
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Uncertainty quantification for nonconvex tensor completion: Confidence
  intervals, heteroscedasticity and optimality
Uncertainty quantification for nonconvex tensor completion: Confidence intervals, heteroscedasticity and optimality
Changxiao Cai
H. Vincent Poor
Yuxin Chen
348
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Tensor Clustering with Planted Structures: Statistical Optimality and
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Tensor Clustering with Planted Structures: Statistical Optimality and Computational Limits
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Anru R. Zhang
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Partially Observed Dynamic Tensor Response Regression
Partially Observed Dynamic Tensor Response RegressionJournal of the American Statistical Association (JASA), 2020
Jie Zhou
W. Sun
Jingfei Zhang
Lexin Li
381
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Regularized and Smooth Double Core Tensor Factorization for
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Regularized and Smooth Double Core Tensor Factorization for Heterogeneous DataJournal of machine learning research (JMLR), 2019
Davoud Ataee Tarzanagh
George Michailidis
462
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Supervised tensor decomposition with features on multiple modes
Supervised tensor decomposition with features on multiple modesJournal of Computational And Graphical Statistics (JCGS), 2019
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Chanwoo Lee
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264
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