Výsledky vyhľadávania - Multi-view data/clustering

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  1. 1

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

    ISSN: 0925-2312, 1872-8286
    Vydavateľské údaje: Elsevier B.V 15.10.2018
    Vydané v Neurocomputing (Amsterdam) (15.10.2018)
    “… Multi-view clustering is an important approach to analyze multi-view data in a unsupervised way…”
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    Journal Article
  2. 2

    Feature decomposition and structural learning for multi-diverse and multi-view data clustering Autor Zhang, Yong, Liu, Da, Jiang, Li, Wang, Huibing, Liu, Wenzhe

    ISSN: 0178-2789, 1432-2315
    Vydavateľské údaje: Berlin/Heidelberg Springer Berlin Heidelberg 01.04.2025
    Vydané v The Visual computer (01.04.2025)
    “…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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    Journal Article
  3. 3

    ORKM: An R package for online multi-view data clustering Autor Yu, Miao, Li, Shu, Guo, Guangbao

    ISSN: 0925-2312
    Vydavateľské údaje: Elsevier B.V 28.01.2026
    Vydané v Neurocomputing (Amsterdam) (28.01.2026)
    “…) 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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  4. 4

    Multi-view data clustering via non-negative matrix factorization with manifold regularization Autor Khan, Ghufran Ahmad, Hu, Jie, Li, Tianrui, Diallo, Bassoma, Wang, Hongjun

    ISSN: 1868-8071, 1868-808X
    Vydavateľské údaje: Berlin/Heidelberg Springer Berlin Heidelberg 01.03.2022
    “… 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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  5. 5

    Unified Multi-view Data Clustering: Simultaneous Learning of Consensus Coefficient Matrix and Similarity Graph Autor Dornaika, F., El Hajjar, S., Charafeddine, J., Barrena, N.

    ISSN: 1866-9956, 1866-9964
    Vydavateľské údaje: New York Springer US 01.02.2025
    Vydané v Cognitive computation (01.02.2025)
    “… However, clustering such multi-view data poses unique challenges due to the heterogeneity and complexity of the data sources…”
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    Journal Article
  6. 6

    A Novel Approach to Learning Consensus and Complementary Information for Multi-View Data Clustering Autor Luong, Khanh, Nayak, Richi

    ISSN: 2375-026X
    Vydavateľské údaje: IEEE 01.04.2020
    Vydané v Data engineering (01.04.2020)
    “…Effective methods are required to be developed that can deal with the multi-faceted nature of the multi-view data…”
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    Konferenčný príspevok..
  7. 7

    An End-to-End Approach for Graph-Based Multi-View Data Clustering Autor Dornaika, Fadi, El Hajjar, Sally

    ISSN: 2332-7790, 2372-2096
    Vydavateľské údaje: Piscataway IEEE 01.10.2024
    Vydané v IEEE transactions on big data (01.10.2024)
    “… 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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  8. 8

    Sampling Enhanced Contrastive Multi-View Remote Sensing Data Clustering With Long-Short Range Information Mining Autor Guan, Renxiang, Liu, Tianrui, Tu, Wenxuan, Tang, Chang, Luo, Wenhan, Liu, Xinwang

    ISSN: 1041-4347, 1558-2191
    Vydavateľské údaje: IEEE 01.09.2025
    “…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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  9. 9

    Deep probability multi-view feature learning for data clustering Autor Zhao, Liang, Wang, Xiao, Liu, Zhenjiao, Yuan, Hong, Zhao, Jingyuan, Zhou, Shuang

    ISSN: 0957-4174, 1873-6793
    Vydavateľské údaje: Elsevier Ltd 01.05.2023
    Vydané v Expert systems with applications (01.05.2023)
    “… other. Thus, many researchers pay more attention to the field of multi-view data clustering…”
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    Journal Article
  10. 10

    Multi-layer manifold learning for deep non-negative matrix factorization-based multi-view clustering Autor Luong, Khanh, Nayak, Richi, Balasubramaniam, Thirunavukarasu, Bashar, Md Abul

    ISSN: 0031-3203, 1873-5142
    Vydavateľské údaje: Elsevier Ltd 01.11.2022
    Vydané v Pattern recognition (01.11.2022)
    “…•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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  11. 11

    Multi-level multi-view network based on structural contrastive learning for scRNA-seq data clustering Autor Shu, Zhenqiu, Xia, Min, Tan, Kaiwen, Zhang, Yongbing, Yu, Zhengtao

    ISSN: 1467-5463, 1477-4054, 1477-4054
    Vydavateľské údaje: England Oxford University Press 23.09.2024
    Vydané v Briefings in bioinformatics (23.09.2024)
    “… 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 Multi-Kernel-Based Multi-View Deep Non-Negative Matrix Factorization for Enhanced Healthcare Data Clustering Autor Che, Hangjun, Yang, Xuanhao

    ISSN: 0098-3063, 1558-4127
    Vydavateľské údaje: New York IEEE 01.02.2025
    “…Multi-view clustering methods based on deep matrix factorization play a vital role in data analysis within the healthcare sector…”
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    Journal Article
  14. 14

    Multi-View Robust Feature Learning for Data Clustering Autor Zhao, Liang, Zhao, Tianyang, Sun, Tingting, Liu, Zhuo, Chen, Zhikui

    ISSN: 1070-9908, 1558-2361
    Vydavateľské údaje: New York IEEE 2020
    “…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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  15. 15

    Learning Inter- and Intra-Manifolds for Matrix Factorization-Based Multi-Aspect Data Clustering Autor Luong, Khanh, Nayak, Richi

    ISSN: 1041-4347, 1558-2191
    Vydavateľské údaje: New York IEEE 01.07.2022
    “…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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    Journal Article
  16. 16

    Multi-View Adaptive Fusion Network for Spatially Resolved Transcriptomics Data Clustering Autor Zhu, Yanran, He, Xiao, Tang, Chang, Liu, Xinwang, Liu, Yuanyuan, He, Kunlun

    ISSN: 1041-4347, 1558-2191
    Vydavateľské údaje: IEEE 01.12.2024
    “… 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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    Journal Article
  17. 17

    Decoupled GNNs based on multi-view contrastive learning for scRNA-seq data clustering Autor Yu, Xiaoyan, Ren, Yixuan, Xia, Min, Shu, Zhenqiu, Zhu, Liehuang

    ISSN: 1467-5463, 1477-4054, 1477-4054
    Vydavateľské údaje: England Oxford University Press 01.05.2025
    Vydané v Briefings in bioinformatics (01.05.2025)
    “… To address these challenges, we propose a novel approach, called decoupled GNNs, based on multi-view contrastive learning (scDeGNN…”
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  18. 18

    Towards unsupervised radiograph clustering for COVID-19: The use of graph-based multi-view clustering Autor Dornaika, F., Hajjar, S. El, Charafeddine, J.

    ISSN: 0952-1976, 1873-6769
    Vydavateľské údaje: Elsevier Ltd 01.07.2024
    “…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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  19. 19

    Virtual label guided multi-view non-negative matrix factorization for data clustering Autor Liu, Xiangyu, Song, Peng

    ISSN: 1051-2004, 1095-4333
    Vydavateľské údaje: Elsevier Inc 01.03.2023
    Vydané v Digital signal processing (01.03.2023)
    “… 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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  20. 20

    Weighted Multi-view Clustering with Feature Selection Autor Xu, Yu-Meng, Wang, Chang-Dong, Lai, Jian-Huang

    ISSN: 0031-3203, 1873-5142
    Vydavateľské údaje: Elsevier Ltd 01.05.2016
    Vydané v Pattern recognition (01.05.2016)
    “…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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    Journal Article