A Novel Low-Rank Embedded Latent Multi-View Subspace Clustering Approach

Noises and outliers often degrade the final prediction performance in practical data processing. Multi-view learning by integrating complementary information across heterogeneous modalities has become one of the core techniques in the field of machine learning. However, existing methods rely on expl...

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Bibliographic Details

Published in:	Sensors
Main Authors:	Sen Wang, Lian Chen, Zhijian Liang, Qingyang Liu
Format:	Article
Language:	English
Published:	MDPI AG 2025-04-01
Subjects:	low-rank embedding multi-view learning heterogeneous feature fusion latent space learning
Online Access:	https://www.mdpi.com/1424-8220/25/9/2778