Self-supervised semantic graph propagation for multi-view clustering

Jiongzhi Qiu

doi:10.1016/j.neunet.2026.108973

2026-04-17

PRE

DOI：10.1016/j.neunet.2026.108973

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摘要

En 中文

• 一种新颖的自监督一致性图传播框架通过整合高置信度伪标签增强了多视图聚类。• 一种视图特定精炼模块通过使用基于KL散度一致性损失的伪标签与视图特定相似性图对齐来增强多视图聚类。• 所提出的方法在多个基准数据集上优于最新的多视图聚类方法。

Keyword:

multi-view clustering

self-supervised learning

graph propagation

pseudo-labels

consistency loss

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Neural Networks

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university of electronic science and technology of china

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