2019 IEEE International Conference on Image Processing (ICIP) 2019
DOI: 10.1109/icip.2019.8803837
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NMF-Based Comprehensive Latent Factor Learning with Multiview Da

Abstract: Multiview representations reveal the latent information of the data from different perspectives, consistency and complementarity. Unlike most multiview learning approaches, which focus only one perspective, in this paper, we propose a novel unsupervised multiview learning algorithm, called comprehensive latent factor learning (CLFL), which jointly exploits both consistent and complementary information among multiple views. CLFL adopts a non-negative matrix factorization based formulation to learn the latent fa… Show more

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Cited by 2 publications
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References 14 publications
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