Inductive multiple clustering based on weakly-supervised salient representation learning

doi:10.1016/j.eswa.2025.129082

Inductive multiple clustering based on weakly-supervised salient representation learning

2025-07-26

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DOI：10.1016/j.eswa.2025.129082

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Abstract

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• IMC is proposed to learn weakly-supervised salient features for multiple clustering. • IMC incorporates sparse and low-rank penalties to highlight salient parts of data. • IMC facilitates intuitive explanations of multiple clustering results. • IMC naturally extends to unseen data clustering by ADMM for the optimization.

Keywords:

IMC

weakly-supervised learning

salient feature extraction

multiple clustering

sparse and low-rank penalties

Inductive multiple clustering based on weakly-supervised salient representation learning

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