Results 231 to 240 of about 24,671,802 (285)
Latent Heterogeneous Graph Network for Incomplete Multi-View Learning
IEEE Transactions on Multimedia, 2023 13 pages, 9 figures, IEEE Transactions on ...
Xinjie Yao, Qinghua Hu, Meng Cao
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Incomplete Multi-View Clustering With Joint Partition and Graph Learning
IEEE Transactions on Knowledge and Data Engineering, 2021 Incomplete multi-view clustering (IMC) aims to integrate the complementary information from incomplete views to improve clustering performance. Most existing IMC methods try to fill the incomplete views or directly learn a common representation based on matrix factorization or subspace learning.
Zhiqiang Wan, Lusi Li, Haibo He
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Projected cross-view learning for unbalanced incomplete multi-view clustering
Information FusionIncomplete multi-view clustering (IMVC) aims to partition samples into different groups for datasets with missing samples. The primary goal of IMVC is to effectively address the challenge posed by missing information in clustering analysis. Most existing
Man-Fai Leung, Hangjun Che, Baicheng Pan
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Incomplete multi-view partial multi-label learning
Applied Intelligence, 2021Partial multi-label learning is of great significant interest due to accurate supervision is difficult to be obtained. Recently, multi-view learning has been developed to deal with partial multi-label learning tasks. Although few multi-view partial multi-label learning methods have been proposed, all of them are designed under the full-view assumption.
Xinyuan Liu 0003 +2 more
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A novel consensus learning approach to incomplete multi-view clustering
Pattern Recognition, 2021Abstract Multi-view data may lose some instances in real applications. Most existing methods for clustering such incomplete multi-view data still have at least one of the following limitations: 1) The common relations among data points across all views are ignored.
Lunke Fei, Xiaozhao Fang, Shaohua Teng
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Dual Contrastive Prediction for Incomplete Multi-View Representation Learning
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022In this article, we propose a unified framework to solve the following two challenging problems in incomplete multi-view representation learning: i) how to learn a consistent representation unifying different views, and ii) how to recover the missing views.
Jiancheng Lv, Xi Peng, Yijie Lin
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Incomplete Multi-View Learning Under Label Shift
IEEE Transactions on Image Processing, 2023In image processing, images are usually composed of partial views due to the uncertainty of collection and how to efficiently process these images, which is called incomplete multi-view learning, has attracted widespread attention. The incompleteness and diversity of multi-view data enlarges the difficulty of annotation, resulting in the divergence of ...
Ruidong Fan +4 more
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Multi-view Multi-label Learning with Incomplete Views and Labels
SN Computer Science, 2021Data set with incomplete information, multi-granularity label correlation when label-specific features and complementarity information provided is ubiquitous in real-world applications. In this paper, we develop a new multi-view multi-label learning with incomplete views and labels (MVML-IVL) for solution and it is the first attempt to design a multi ...
Changming Zhu, Lin Ma
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Tensor-based consensus learning for incomplete multi-view clustering
Expert Systems With Applications, 2023Yanwei Yu, Peng Song
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A new multi-view learning machine with incomplete data
Pattern Analysis and Applications, 2020Multi-view learning with incomplete views (MVL-IV) is a reliable algorithm to process incomplete datasets which consist of instances with missing views or features. In MVL-IV, it exploits the connections among multiple views and suggests that different views are generated from a shared subspace such that it can recover the missing views or features ...
Changming Zhu +4 more
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