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Deep Spectral Representation Learning From Multi-View Data
IEEE Transactions on Image Processing, 2021Multi-view representation learning (MvRL) aims to learn a consensus representation from diverse sources or domains to facilitate downstream tasks such as clustering, retrieval, and classification. Due to the limited representative capacity of the adopted shallow models, most existing MvRL methods may yield unsatisfactory results, especially when the ...
Zhenyu Huang +5 more
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Robust multi-view data clustering with multi-view capped-norm K-means
Neurocomputing, 2018Abstract Real-world data sets are often comprised of multiple representations or views which provide different and complementary aspects of information. Multi-view clustering is an important approach to analyze multi-view data in a unsupervised way.
Shudong Huang, Yazhou Ren, Zenglin Xu
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Binary spectral clustering for multi-view data
Information ScienceszbMATH Open Web Interface contents unavailable due to conflicting licenses.
Xueming Yan +5 more
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Feature selection with multi-view data: A survey
Information Fusion, 2019This survey aims at providing a state-of-the-art overview of feature selection and fusion strategies, which select and combine multi-view features effectively to accomplish associated tasks.
Rui Zhang, F. Nie, Xuelong Li, Xian Wei
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Unsupervised and Semi-Supervised Learning, 2018
Multi-view learning has been explored in various applications such as bioinformatics, natural language processing and multimedia analysis. Often multi-view learning methods commonly assume that full feature matrices or kernel matrices for all views are available. However, in partial data analytics, it is common that information from some sources is not
Sahely Bhadra
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Multi-view learning has been explored in various applications such as bioinformatics, natural language processing and multimedia analysis. Often multi-view learning methods commonly assume that full feature matrices or kernel matrices for all views are available. However, in partial data analytics, it is common that information from some sources is not
Sahely Bhadra
openaire +2 more sources
Towards metric fusion on multi-view data
Proceedings of the 22nd ACM international conference on Information & Knowledge Management, 2013Many real-world objects described by multiple attributes or features can be decomposed as multiple "views" (e.g., an image can be described by a color view or a shape view), which often provides complementary information to each other. Learning a metric (similarity measures) for multi-view data is primary due to its wide applications in practices ...
Yang Wang, Xuemin Lin, Qing Zhang
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Diverse Deep Matrix Factorization with Hypergraph Regularization for Multi-View Data Representation
IEEE/CAA Journal of Automatica Sinica, 2023Deep matrix factorization (DMF) has been demon-strated to be a powerful tool to take in the complex hierarchical information of multi-view data (MDR).
Haonan Huang +4 more
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Self-Representation Subspace Clustering for Incomplete Multi-view Data
ACM Multimedia, 2021Incomplete multi-view clustering is an important research topic in multimedia where partial data entries of one or more views are missing. Current subspace clustering approaches mostly employ matrix factorization on the observed feature matrices to ...
Jiyuan Liu +9 more
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