Latent Structure-Aware View Recovery for Incomplete Multi-View Clustering

Incomplete multi-view clustering (IMVC) presents a significant challenge due to the need for effectively exploring complementary and consistent information within the context of missing views. One promising strategy to tackle this challenge is to recover missing views by inferring the missing sample...

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Veröffentlicht in:	IEEE transactions on knowledge and data engineering 2024-12, Vol.36 (12), p.8655-8669
Hauptverfasser:	Liu, Cheng, Li, Rui, Che, Hangjun, Leung, Man-Fai, Wu, Si, Yu, Zhiwen, Wong, Hau-San
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Computer science cross view graph diffusion regularization Diffusion processes Imputation Incomplete multi-view clustering (IMVC) Iterative methods latent structure-aware view recovery (LaSA) Optimization Representation learning
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