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Journal of the American Statistical Association Volume 117, 2022 - Issue 540
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Theory and Methods

A Doubly Enhanced EM Algorithm for Model-Based Tensor Clustering

Qing MaiDepartment of Statistics, Florida State University, Tallahassee, FL
,
Xin ZhangDepartment of Statistics, Florida State University, Tallahassee, FLCorrespondence[email protected]
,
Yuqing PanDepartment of Statistics, Florida State University, Tallahassee, FL
&
Kai DengDepartment of Statistics, Florida State University, Tallahassee, FL
Pages 2120-2134 | Received 19 Jan 2020, Accepted 08 Mar 2021, Published online: 04 May 2021

Citations (9)

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Read on this site (1)

Junge Li & Qing Mai. (2024) Model-Based Tensor Low-Rank Clustering. Journal of Computational and Graphical Statistics 33:1, pages 208-218.
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Articles from other publishers (8)

Xuesong Hou, Qing Mai & Hui Zou. (2024) Tensor mixture discriminant analysis with applications to sensor array data analysis. The Annals of Applied Statistics 18:1.
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Salvatore D. Tomarchio, Antonio Punzo & Luca Bagnato. (2023) Parsimonious mixtures for the analysis of tensor-variate data. Statistics and Computing 33:6.
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Keqian Min, Qing Mai & Junge Li. (2023) Optimality in high-dimensional tensor discriminant analysis. Pattern Recognition 143, pages 109803.
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Jiaxing Zhang. (2023) Research on the Application of Trade Gravity Model in the National Bilateral Export Trade. Research on the Application of Trade Gravity Model in the National Bilateral Export Trade.
Zhongyuan Lyu & Dong Xia. (2023) Optimal estimation and computational limit of low-rank Gaussian mixtures. The Annals of Statistics 51:2.
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Kunpeng Jiang, Huifang Guo, Kun Yang, Haipeng Qu, Miao Li & Liming Wang. (2022) An self-adaptive cluster centers learning algorithm based on expectation maximization algorithm. An self-adaptive cluster centers learning algorithm based on expectation maximization algorithm.
Kai Deng & Xin Zhang. (2021) Tensor envelope mixture model for simultaneous clustering and multiway dimension reduction. Biometrics 78:3, pages 1067-1079.
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Wei Luo. (2022) Determine the number of clusters by data augmentation. Electronic Journal of Statistics 16:2.
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