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Correction to "Mitral regurgitation detection and central/eccentric classification using transformer-based deep learning in multi-view echocardiography". [PDF]
J Appl Clin Med Physeuropepmc +1 more source
Biased Incomplete Multi-View Learning [PDF]
Proceedings of the AAAI Conference on Artificial IntelligenceConsidering the ubiquitous phenomenon of missing views in multi-view data, incomplete multi-view learning is a crucial task in many applications. Existing methods usually follow an impute-then-predict strategy for handling this problem. However, they often assume that the view-missing patterns are uniformly random in multi-view data, which does not ...
Haishun Chen +4 more
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A survey of multi-view machine learning
Neural Computing and Applications, 2013Multi-view learning or learning with multiple distinct feature sets is a rapidly growing direction in machine learning with well theoretical underpinnings and great practical success. This paper reviews theories developed to understand the properties and behaviors of multi-view learning and gives a taxonomy of approaches according to the machine ...
Shiliang Sun, Sun Shiliang
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Unbalanced Multi-view Deep Learning [PDF]
Proceedings of the 31st ACM International Conference on Multimedia, 2023 Most existing multi-view learning methods assume that the dimensions of different views are similar. In real-world applications, it is often the case that the dimension of a view may be extremely small compared with these of other views, resulting in an ...
Cai Xu +6 more
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Comprehensive Multi-view Representation Learning
Information Fusion, 2023Qinghai Zheng +2 more
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Contrastive Multi-View Kernel Learning
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023Kernel method is a proven technique in multi-view learning. It implicitly defines a Hilbert space where samples can be linearly separated. Most kernel-based multi-view learning algorithms compute a kernel function aggregating and compressing the views into a single kernel.
Jiyuan Liu 0003 +4 more
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Efficient federated multi-view learning [PDF]
Pattern Recognition, 2022 Multi-view learning aims to explore a global common structure shared by different views collected from multiple individual sources. The nascent field of federated learning tries to learn a global model over distributed networks of devices.
Shudong Huang +4 more
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Multi-view learning with Universum
Knowledge-Based Systems, 2014The traditional Multi-view Learning (MVL) studies how to process patterns with multiple information sources. In practice, the MVL is proven to have a significant advantage over the Single-view Learning (SVL). But in most real-world cases, there are only single-source patterns to be dealt with and the existing MVL is unable to be directly applied.
Zhe Wang 0002 +4 more
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Multi-view representation learning for multi-view action recognition
Journal of Visual Communication and Image Representation, 2017This approach directly exploits the relationships among different action categories from different views.We bridge the gap of the sparsity representation of different actions from the different views.This approach explores the task of cross-view recognition.
Tong Hao +3 more
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Multi-view Proximity Learning for Clustering
2018In recent years, multi-view clustering has become a hot research topic due to the increasing amount of multi-view data. Among existing multi-view clustering methods, proximity-based method is a typical class and achieves much success. Usually, these methods need proximity matrices as inputs, which can be constructed by some nearest-neighbors-based ...
Kun-Yu Lin +3 more
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