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Tensor Principal Component Analysis in High Dimensional CP Models

Tensor Principal Component Analysis in High Dimensional CP Models

10 August 2021
Yuefeng Han
Cun-Hui Zhang
ArXivPDFHTML

Papers citing "Tensor Principal Component Analysis in High Dimensional CP Models"

6 / 6 papers shown
Title
TEAFormers: TEnsor-Augmented Transformers for Multi-Dimensional Time
  Series Forecasting
TEAFormers: TEnsor-Augmented Transformers for Multi-Dimensional Time Series Forecasting
Linghang Kong
Elynn Chen
Yuzhou Chen
Yuefeng Han
AI4TS
26
0
0
27 Oct 2024
Factor Augmented Tensor-on-Tensor Neural Networks
Factor Augmented Tensor-on-Tensor Neural Networks
Guanhao Zhou
Yuefeng Han
Xiufan Yu
27
1
0
30 May 2024
Deflated HeteroPCA: Overcoming the curse of ill-conditioning in
  heteroskedastic PCA
Deflated HeteroPCA: Overcoming the curse of ill-conditioning in heteroskedastic PCA
Yuchen Zhou
Yuxin Chen
38
4
0
10 Mar 2023
Rank and Factor Loadings Estimation in Time Series Tensor Factor Model
  by Pre-averaging
Rank and Factor Loadings Estimation in Time Series Tensor Factor Model by Pre-averaging
Weilin Chen
Clifford Lam
11
11
0
08 Aug 2022
Modelling matrix time series via a tensor CP-decomposition
Modelling matrix time series via a tensor CP-decomposition
Jinyuan Chang
Jingjing He
Lin Yang
Q. Yao
AI4TS
23
29
0
31 Dec 2021
Low-rank Tensor Estimation via Riemannian Gauss-Newton: Statistical
  Optimality and Second-Order Convergence
Low-rank Tensor Estimation via Riemannian Gauss-Newton: Statistical Optimality and Second-Order Convergence
Yuetian Luo
Anru R. Zhang
40
18
0
24 Apr 2021
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