Multi-view subspace clustering based on low-rank tensor and angular information(基于低秩张量和角度信息的多视图子空间聚类)

∶Existing tensor-based multi-view subspace clustering methods have achieved remarkable success. However, these methods generally suffer from issues such as equivalent regularization of singular values and suboptimal construction of similarity matrices, which limit their performance. To address these...

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Bibliographic Details
Main Authors: 张沙沙(ZHANG Shasha), 王长鹏(WANG Changpeng)
Format: Article
Language:zho
Published: Zhejiang University Press 2025-05-01
Series:Zhejiang Daxue xuebao. Lixue ban
Online Access:https://doi.org/10.3785/j.issn.1008-9497.2025.03.005
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