Sparse Subspace Clustering Based on Adaptive Parameter Training - Intelligent Information Processing XI
Conference Papers Year : 2022

Sparse Subspace Clustering Based on Adaptive Parameter Training

Min Li
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Abstract

There are many researches on sparse subspace clustering, but there are few related studies on its parameter optimization. In this paper, we propose an adaptive training parameter method to improve the manual selection process of convex optimization regularization parameters and improve the accuracy of subspace clustering. Experiments were carried out on multiple datasets, and the clustering accuracy is improved. The results prove that the improved parameter training process can improve the clustering accuracy of subspace clustering.
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Dates and versions

hal-04178750 , version 1 (08-08-2023)

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Kexuan Zhu, Min Li. Sparse Subspace Clustering Based on Adaptive Parameter Training. 12th International Conference on Intelligent Information Processing (IIP), May 2022, Qingdao, China. pp.56-64, ⟨10.1007/978-3-031-03948-5_5⟩. ⟨hal-04178750⟩
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