IBMvSVM: An instance-based multi-view SVM algorithm for classification-Reference-Cited by-同舟云学术

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IBMvSVM: An instance-based multi-view SVM algorithm for classification

Published:2022-02-10 Issue:13 Volume:52 Page:14739-14755
ISSN:0924-669X
Container-title:Applied Intelligence
language:en
Short-container-title:Appl Intell

Author:

Yu Shuang^ORCID,Li Xiongfei,Sun Siru,Wang Hancheng,Zhang Xiaoli,Chen Shiping

Funder

National Natural Science Foundation of China

Natural Science Foundation of Jilin Province

Foundation for Distinguished Young Talents in Higher Education of Guangdong (CN)Outstanding Young Talent Foundation of Jilin Province

Industrial Technology Research and Development Funds of Jilin Province

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence

Link

https://link.springer.com/content/pdf/10.1007/s10489-021-03101-y.pdf

Reference47 articles.

1. Achanta HK, Misganaw B, Vidyasagar M (2017) A multi-view $$\ell$$ 1-norm svm algorithm for data integration in biological applications. In: 2017 American control conference (ACC), IEEE, pp 3753–3757

2. Bekker AJ, Shalhon M, Greenspan H, Goldberger J (2015) Multi-view probabilistic classification of breast microcalcifications. IEEE Trans Med Imag 35(2):645–653

3. van Breukelen M, Duin RP, Tax DM, Den Hartog J (1998) Handwritten digit recognition by combined classifiers. Kybernetika 34(4):381–386

4. Chao G, Sun S (2016) Consensus and complementarity based maximum entropy discrimination for multi-view classification. Inform Sci 367:296–310

5. Chen N, Zhu J, Sun F, Xing EP (2012) Large-margin predictive latent subspace learning for multiview data analysis. IEEE Trans Pattern Anal Mach Intell 34(12):2365–2378

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2. Kernel-Free Nonlinear Support Vector Machines for Multiview Binary Classification Problems;International Journal of Intelligent Systems;2023-05-02

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