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CONAN: Contrastive Fusion Networks for Multi-view Clustering

2021 IEEE International Conference on Big Data (Big Data)(2021)

Cited 7|Views28
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Abstract
With the development of big data, deep learning has made remarkable progress on multi-view clustering. Multi-view fusion is a crucial technique for the model obtaining a common representation. However, existing literature adopts shallow fusion strategies, such as weighted-sum fusion and concatenating fusion, which fail to capture complex information from multiple views. In this paper, we propose a...
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Key words
Deep learning,Codes,Clustering methods,Conferences,Big Data,Data mining,Task analysis
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