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Inference for Low-rank Tensors -- No Need to Debias
v1v2 (latest)

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

Annals of Statistics (Ann. Stat.), 2020
29 December 2020
Dong Xia
Anru R. Zhang
Yuchen Zhou
ArXiv (abs)PDFHTML

Papers citing "Inference for Low-rank Tensors -- No Need to Debias"

15 / 15 papers shown
Perfect Clustering in Very Sparse Diverse Multiplex Networks
Perfect Clustering in Very Sparse Diverse Multiplex Networks
Marianna Pensky
186
0
0
25 Jul 2025
Theoretical Guarantees for Low-Rank Compression of Deep Neural Networks
Theoretical Guarantees for Low-Rank Compression of Deep Neural Networks
Shihao Zhang
Rayan Saab
173
2
0
04 Feb 2025
Statistical Inference on High Dimensional Gaussian Graphical Regression
  Models
Statistical Inference on High Dimensional Gaussian Graphical Regression Models
Xuran Meng
Jingfei Zhang
Yi Li
247
1
0
03 Nov 2024
Conditional Uncertainty Quantification for Tensorized Topological Neural
  Networks
Conditional Uncertainty Quantification for Tensorized Topological Neural Networks
Yujia Wu
Bo Yang
Yang Zhao
Elynn Chen
Yuzhou Chen
Zheshi Zheng
246
3
0
20 Oct 2024
Tensor-Fused Multi-View Graph Contrastive Learning
Tensor-Fused Multi-View Graph Contrastive LearningPacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2024
Yujia Wu
Junyi Mo
Elynn Chen
Yuzhou Chen
313
1
0
20 Oct 2024
Low-Rank Online Dynamic Assortment with Dual Contextual Information
Low-Rank Online Dynamic Assortment with Dual Contextual Information
Seong Jin Lee
Will Wei Sun
Yufeng Liu
262
1
0
19 Apr 2024
Inference of Dependency Knowledge Graph for Electronic Health Records
Inference of Dependency Knowledge Graph for Electronic Health Records
Zhiwei Xu
Ziming Gan
Doudou Zhou
Shuting Shen
Junwei Lu
Tianxi Cai
329
4
0
25 Dec 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
389
12
0
09 Oct 2023
Deflated HeteroPCA: Overcoming the curse of ill-conditioning in
  heteroskedastic PCA
Deflated HeteroPCA: Overcoming the curse of ill-conditioning in heteroskedastic PCAAnnals of Statistics (Ann. Stat.), 2023
Yuchen Zhou
Yuxin Chen
341
10
0
10 Mar 2023
On the Multiway Principal Component Analysis
On the Multiway Principal Component Analysis
Jialin Ouyang
Ming Yuan
302
3
0
14 Feb 2023
Graphical Model Inference with Erosely Measured Data
Graphical Model Inference with Erosely Measured DataJournal of the American Statistical Association (JASA), 2022
Lili Zheng
Genevera I. Allen
276
2
0
20 Oct 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
489
4
0
11 Jul 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
363
25
0
17 Jun 2022
Scaling and Scalability: Provable Nonconvex Low-Rank Tensor Estimation
  from Incomplete Measurements
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
422
45
0
29 Apr 2021
Generalized Low-rank plus Sparse Tensor Estimation by Fast Riemannian
  Optimization
Generalized Low-rank plus Sparse Tensor Estimation by Fast Riemannian OptimizationJournal of the American Statistical Association (JASA), 2021
Jian-Feng Cai
Jingyang Li
Dong Xia
643
35
0
16 Mar 2021
1
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