Tensorized anchor alignment for incomplete multi-view clustering

Yiran Cai

doi:10.1016/j.neunet.2025.107981

Tensorized anchor alignment for incomplete multi-view clustering

2025-08-13

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DOI：10.1016/j.neunet.2025.107981

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• The paper introduces a tensorized anchor alignment framework for large-scale incomplete multi-view clustering. • The view-specific anchor graphs are constructed to reduce computational burden while capturing complementary information across views. • The binary alignment matrix is incorporated to align anchor graphs across views and mitigate misalignment effects. • Tensor-based low-rank constraint is employed to capture the high-order correlations among views.

Keywords:

Anchor graph learning

Incomplete multi-view clustering

Low-rank tensor learning

High-order correlation

Tensorized anchor alignment for incomplete multi-view clustering

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