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Deep non-negative matrix factorization with multi-layer graph regularization for clustering
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DOI：10.1016/j.patcog.2026.113325.png)
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Abstract
En 中文
• A multi-layer graph regularization is introduced for the first time. • A graph regularized deep NMF method is proposed. • A seminsupervised graph regularized deep NMF method is developed. • Numerous experiments show the superiority of the proposed methods.
Keywords:
deep non-negative matrix factorization
multi-layer graph regularization
clustering
semi-supervised learning
dimensionality reduction
Journal
IF:
7.6
Papers:
1.3W
Citations:
4.5W
Organization
Cited Papers
Semi-supervised nonnegative matrix factorization with label propagation and constraint propagation
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ShareSaveShareSaveGraph regularized nonnegative matrix factorization with label discrimination for data clusteringNEUROCOMPUTING
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ShareSaveShareSaveShareSaveHypergraph based semi-supervised symmetric nonnegative matrix factorization for image clusteringPATTERN RECOGNITION
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