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Multi-view clustering via dual-norm and HSIC

  • 1230: Sentient Multimedia Systems and Visual Intelligence
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Abstract

Fully capturing valid complementary information in multi-view data enhances the connection between similar data points and weakens the correlation between different data point categories. In this paper, we propose a new multi-view clustering via dual-norm and Hilbert-Schmidt independence criterion (HSIC) induction (MCDHSIC) approach, which can enhance the complementarity, reduce the redundancy between multi-view representations, and improve the accuracy of the clustering results. This model uses the HSIC as the diversity regularization term to capture the nonlinear relationship between different views. In addition, l1-norm and Frobenius norm constraints are imposed to obtain a subspace representation matrix with inter-class sparsity and intra-class consistency. Moreover, we also designed a valuable approach to optimizing the proposed model and theoretically analyzing the convergence of the MCDHSIC method. The results of extensive experiments conducted on five challenging data sets show that the proposed method objectively achieves a highly competent performance compared with several other state-of-the-art multi-view clustering methods.

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Acknowledgments

The National Natural Science Foundation of China under Grants 61806006, China Postdoctoral Science Foundation under Grant No. 2019 M660149, the 111 Project under Grants No. B12018, and PAPD of Jiangsu Higher Education Institutions support this work. Guoqing Liu: Conceptualization, Methodology, Validation, Software, Formal analysis, Data curation, Investigation, Writing–original draft. Hongwei Ge: Resources, Review, Supervision, Project administration, Funding acquisition. Shuzhi Su: Review. Shuangxi Wang: Software, Visualization.

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Authors and Affiliations

  1. School of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi, 214122, Jiangsu, China

    Guoqing Liu, Hongwei Ge & Shuangxi Wang

  2. Key Laboratory of Advanced Process Control for Light Industry, Jiangnan University, Ministry of Education, Wuxi, 214122, China

    Guoqing Liu, Hongwei Ge & Shuangxi Wang

  3. School of Computer Science and Engineering, Anhui University of Science & Technology, Huainan, 232001, Anhui, China

    Shuzhi Su

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  1. Guoqing Liu
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Correspondence to Hongwei Ge.

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Liu, G., Ge, H., Su, S. et al. Multi-view clustering via dual-norm and HSIC. Multimed Tools Appl 83, 36399–36418 (2024). https://doi.org/10.1007/s11042-022-14057-7

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