Multiview Clustering via Block Diagonal Graph Filtering | IEEE Journals & Magazine | IEEE Xplore

Multiview Clustering via Block Diagonal Graph Filtering


Abstract:

Graph-based multiview clustering methods have gained significant attention in recent years. In particular, incorporating graph filtering into these methods allows for the...Show More

Abstract:

Graph-based multiview clustering methods have gained significant attention in recent years. In particular, incorporating graph filtering into these methods allows for the exploration and utilization of both feature and topological information, resulting in a commendable improvement in clustering accuracy. However, these methods still exhibit several limitations: 1) the graph filters are predetermined, which disconnects the link with subsequent clustering tasks and 2) the separability of the filtered features is poor, which may not be suitable for the clustering. To mitigate these aforementioned issues, we propose Multiview Clustering via Block Diagonal Graph Filtering (MvC-BDGF), which can learn cluster-friendly graph filters. Specifically, the block diagonal graph filter with localized characteristics, which could make the filtered features very discriminating, is innovatively designed. The MvC-BDGF model seamlessly integrates the learning of graph filters with the acquisition of consensus graphs, forming a unified framework. This integration allows the model to obtain optimal filters and simultaneously acquire corresponding clustering labels. To solve the optimization problem in the MvC-BDGF model, an iterative solver based on the coordinate descent method is devised. Finally, a large number of experiments on benchmark datasets fully demonstrate the effectiveness and superiority of the proposed model. The code is available at https://github.com/haonanxin/MvC-BDGF_code.
Page(s): 1 - 14
Date of Publication: 04 March 2025

ISSN Information:

PubMed ID: 40036519

Funding Agency:

Optics and Electronics (iOPEN) and the Key Laboratory of Intelligent Interaction and Applications (Ministry of Industry and Information Technology), School of Artificial Intelligence, Northwestern Polytechnical University, Xi’an, Shaanxi, China
College of Information Engineering, Northwest A and F University, Xianyang, China
the School of Artificial Intelligence, Optics and Electronics (iOPEN), and the Key Laboratory of Intelligent Interaction and Applications (Ministry of Industry and Information Technology), School of Computer Science, Northwestern Polytechnical University, Xi’an, Shaanxi, China
Optics and Electronics (iOPEN) and the Key Laboratory of Intelligent Interaction and Applications (Ministry of Industry and Information Technology), School of Artificial Intelligence, Northwestern Polytechnical University, Xi’an, Shaanxi, China
the School of Artificial Intelligence, Optics and Electronics (iOPEN), and the Key Laboratory of Intelligent Interaction and Applications (Ministry of Industry and Information Technology), School of Computer Science, Northwestern Polytechnical University, Xi’an, Shaanxi, China
Institute of Artificial Intelligence, China Telecom Corporation Ltd, Beijing, China

Optics and Electronics (iOPEN) and the Key Laboratory of Intelligent Interaction and Applications (Ministry of Industry and Information Technology), School of Artificial Intelligence, Northwestern Polytechnical University, Xi’an, Shaanxi, China
College of Information Engineering, Northwest A and F University, Xianyang, China
the School of Artificial Intelligence, Optics and Electronics (iOPEN), and the Key Laboratory of Intelligent Interaction and Applications (Ministry of Industry and Information Technology), School of Computer Science, Northwestern Polytechnical University, Xi’an, Shaanxi, China
Optics and Electronics (iOPEN) and the Key Laboratory of Intelligent Interaction and Applications (Ministry of Industry and Information Technology), School of Artificial Intelligence, Northwestern Polytechnical University, Xi’an, Shaanxi, China
the School of Artificial Intelligence, Optics and Electronics (iOPEN), and the Key Laboratory of Intelligent Interaction and Applications (Ministry of Industry and Information Technology), School of Computer Science, Northwestern Polytechnical University, Xi’an, Shaanxi, China
Institute of Artificial Intelligence, China Telecom Corporation Ltd, Beijing, China

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