硕士生导师
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学历：博士研究生毕业
学位：工学博士学位
办公地点：犀浦3号教学楼31529
毕业院校：四川大学
学科：电子信息. 软件工程. 计算机应用技术
所在单位：计算机与人工智能学院
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Multi-view Clustering for Multiple Manifold Learning via Concept Factorization
DOI码：10.1016/j.dsp.2023.104118
所属单位：西南交通大学
发表刊物：Digital Signal Processing
刊物所在地：UNITED STATES
关键字：Multi-view clustering; Concept factorization; Consensus manifold; Correlation constraint
摘要：Clustering of multi-view data has attracted great interest in machine learning. Multi-view data is based on complementary and consistent information due to the collection of numerous sources. However, the current multi-view clustering method does not focus on learning the manifold structure for consensus representation over the kernel space, the overfitting redundant features of diverse view data, and ignoring the correlation among these complementary multiple views. In this article, a novel multi-view clustering approach is introduced to tackle this issue, which deploys concept factorization to indulge the intrinsic data information. The intrinsic geometry of the data and consensus representation are preserved through the utilization of manifold learning. In addition, the correlation constraint is adopted for learning the common shared structure from diverse views, and the smooth regularization term is deployed to alleviate the overfitting of views. Finally, we fuse all individual terms to formulate the objective function and design a theoretically guaranteed optimization procedure to solve the model. Extensive experiments conducted on the benchmark datasets suggest that the proposed algorithm surpasses state-of-the-art approaches regarding clustering performance.
合写作者：Tianrui Li,Bassoma Diallo,Hongjun Wang
第一作者：Ghufran Ahmad Khan
论文类型：SCI
通讯作者：Jie Hu
学科门类：工学
文献类型：J
卷号：140
页面范围：104118
是否译文：否
发表时间：2023-06-05
收录刊物：SCI