Robust capped norm dual hyper-graph regularized non-negative matrix tri-factorization

Robust capped norm dual hyper-graph regularized non-negative matrix tri-factorization

Non-negative matrix factorization (NMF) has been widely used in machine learning and data mining fields. As an extension of NMF, non-negative matrix tri-factorization (NMTF) provides more degrees of freedom than NMF. However, standard NMTF algorithm utilizes Frobenius norm to calculate residual erro...

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Bibliographic Details
Main Authors: Jiyang Yu, Baicheng Pan, Shanshan Yu, Man-Fai Leung
Format: Article
Language:English
Published: AIMS Press 2023-05-01
Series:Mathematical Biosciences and Engineering
Subjects:
non-negative matrix tri-factorization
capped norm
dual hyper-graph regularization
robust clustering
Online Access:https://www.aimspress.com/article/doi/10.3934/mbe.2023556?viewType=HTML

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https://www.aimspress.com/article/doi/10.3934/mbe.2023556?viewType=HTML

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