Search Results - Multi-view data/clustering

Robust multi-view data clustering with multi-view capped-norm K-means by Huang, Shudong, Ren, Yazhou, Xu, Zenglin

“… Multi-view clustering is an important approach to analyze multi-view data in a unsupervised way…”
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Feature decomposition and structural learning for multi-diverse and multi-view data clustering by Zhang, Yong, Liu, Da, Jiang, Li, Wang, Huibing, Liu, Wenzhe

“…In recent years, real-world data often encompass multiple views or features, making multi-view clustering into the spotlight of research…”
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ORKM: An R package for online multi-view data clustering by Yu, Miao, Li, Shu, Guo, Guangbao

“…) method for handling online multi-view or single-view data, which named ORKMeans function in the package incorporates a regularization term to address multi-view clustering problems with online updates…”
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Multi-view data clustering via non-negative matrix factorization with manifold regularization by Khan, Ghufran Ahmad, Hu, Jie, Li, Tianrui, Diallo, Bassoma, Wang, Hongjun

“… However, NMF does not focus to conserve the geometrical structures of the data space. In this article, we intensify on the above issue and evolve a new NMF clustering method with manifold regularization for multi-view data…”
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Unified Multi-view Data Clustering: Simultaneous Learning of Consensus Coefficient Matrix and Similarity Graph by Dornaika, F., El Hajjar, S., Charafeddine, J., Barrena, N.

“… However, clustering such multi-view data poses unique challenges due to the heterogeneity and complexity of the data sources…”
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A Novel Approach to Learning Consensus and Complementary Information for Multi-View Data Clustering by Luong, Khanh, Nayak, Richi

“…Effective methods are required to be developed that can deal with the multi-faceted nature of the multi-view data…”
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An End-to-End Approach for Graph-Based Multi-View Data Clustering by Dornaika, Fadi, El Hajjar, Sally

“… In response to this limitation, and with an emphasis on advocating end-to-end solutions for multi-view clustering, two comprehensive approaches are presented in this paper…”
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Sampling Enhanced Contrastive Multi-View Remote Sensing Data Clustering With Long-Short Range Information Mining by Guan, Renxiang, Liu, Tianrui, Tu, Wenxuan, Tang, Chang, Luo, Wenhan, Liu, Xinwang

“…Multi-view clustering (MVC) for remote sensing data has demonstrated significant potential in Earth observation, given its ability to aggregate multi-source information without relying on labels…”
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Deep probability multi-view feature learning for data clustering by Zhao, Liang, Wang, Xiao, Liu, Zhenjiao, Yuan, Hong, Zhao, Jingyuan, Zhou, Shuang

“… other. Thus, many researchers pay more attention to the field of multi-view data clustering…”
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Multi-layer manifold learning for deep non-negative matrix factorization-based multi-view clustering by Luong, Khanh, Nayak, Richi, Balasubramaniam, Thirunavukarasu, Bashar, Md Abul

“…•The T-SNE visualizations of the features learned by the proposed Deep-NMF and its counterpart ascertain the effectiveness of the proposed framework for multi-view clustering…”
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Multi-level multi-view network based on structural contrastive learning for scRNA-seq data clustering by Shu, Zhenqiu, Xia, Min, Tan, Kaiwen, Zhang, Yongbing, Yu, Zhengtao

“… These deep multi-view data serve as the input for representation learning. To improve the clustering performance of scRNA-seq data, contrastive…”
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A framework for scRNA-seq data clustering based on multi-view feature integration by Li, Feng, Liu, Yang, Liu, Jinxing, Ge, Daohui, Shang, Junliang

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A Multi-Kernel-Based Multi-View Deep Non-Negative Matrix Factorization for Enhanced Healthcare Data Clustering by Che, Hangjun, Yang, Xuanhao

“…Multi-view clustering methods based on deep matrix factorization play a vital role in data analysis within the healthcare sector…”
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Multi-View Robust Feature Learning for Data Clustering by Zhao, Liang, Zhao, Tianyang, Sun, Tingting, Liu, Zhuo, Chen, Zhikui

“…Multi-view feature learning can provide basic information for consistent grouping, and is very common in practical applications, such as judicial document clustering…”
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Learning Inter- and Intra-Manifolds for Matrix Factorization-Based Multi-Aspect Data Clustering by Luong, Khanh, Nayak, Richi

“…Clustering on the data with multiple aspects, such as multi-view or multi-type relational data, has become popular in recent years due to their wide applicability…”
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Multi-View Adaptive Fusion Network for Spatially Resolved Transcriptomics Data Clustering by Zhu, Yanran, He, Xiao, Tang, Chang, Liu, Xinwang, Liu, Yuanyuan, He, Kunlun

“… To this end, we propose an end-to-end deep learning method named MAFN for spatially resolved transcriptomics data clustering via a multi-view adaptive fusion network…”
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Decoupled GNNs based on multi-view contrastive learning for scRNA-seq data clustering by Yu, Xiaoyan, Ren, Yixuan, Xia, Min, Shu, Zhenqiu, Zhu, Liehuang

“… To address these challenges, we propose a novel approach, called decoupled GNNs, based on multi-view contrastive learning (scDeGNN…”
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Towards unsupervised radiograph clustering for COVID-19: The use of graph-based multi-view clustering by Dornaika, F., Hajjar, S. El, Charafeddine, J.

“…Automatic classification methods widely used for diagnosing and analyzing COVID-19 cases. These methods assume known labels and rely on a single view of the…”
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Virtual label guided multi-view non-negative matrix factorization for data clustering by Liu, Xiangyu, Song, Peng

“… However, it remains challenging when handling multi-view data for clustering. On one hand, the current multi-view NMF methods do not fully utilize the virtual label information that can be learned in the clustering process…”
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Weighted Multi-view Clustering with Feature Selection by Xu, Yu-Meng, Wang, Chang-Dong, Lai, Jian-Huang

“…In recent years, combining multiple sources or views of datasets for data clustering has been a popular practice for improving clustering accuracy…”
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