Cross-view collaborative learning and flexible embedding representation for unsupervised multi-view feature selection

doi:10.1016/j.eswa.2026.132417

Cross-view collaborative learning and flexible embedding representation for unsupervised multi-view feature selection

2026-04-15

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DOI：10.1016/j.eswa.2026.132417

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Abstract

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• A multi-view embedding framework learns embeddings from a shared low-dimensional subspace. • A cross-view collaboration scheme obtains a consensus graph from the flexible embeddings. • The self-weighted preserves local structure and captures the importance/diversity of views.

Keywords:

multi-view embedding

cross-view collaboration

unsupervised feature selection

flexible representation

consensus graph

Cross-view collaborative learning and flexible embedding representation for unsupervised multi-view feature selection

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