Matrix normal PCA for interpretable dimension reduction and graphical noise modeling-Reference-Cited by-同舟云学术

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Matrix normal PCA for interpretable dimension reduction and graphical noise modeling

Published:2024-10 Issue: Volume:154 Page:110591
ISSN:0031-3203
Container-title:Pattern Recognition
language:en
Short-container-title:Pattern Recognition

Author:

Zhang Chihao,Gai Kuo,Zhang Shihua^ORCID

Publisher

Elsevier BV

Reference40 articles.

1. Robust principal component analysis: exact recovery of corrupted low-rank matrices via convex optimization;Wright,2009

2. Robust principal component analysis?;Candès;J. ACM,2011

3. Elastic nonnegative matrix factorization;Xiong;Pattern Recognit.,2019

4. Robust semi-supervised nonnegative matrix factorization for image clustering;Peng;Pattern Recognit.,2021

5. Self-paced principal component analysis;Kang;Pattern Recognit.,2023

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1. Classification of Fritillaria using a portable near-infrared spectrometer and fuzzy generalized singular value decomposition;Industrial Crops and Products;2024-10

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