Multimodal correlation deep belief networks for multi-view classification

doi:10.1007/s10489-018-1379-8

	Multimodal correlation deep belief networks for multi-view classification
	Zhang, Nan 1; Ding, Shifei 1,2; Liao, Hongmei 1; Jia, Weikuan 3
	2019-05-01
发表期刊	APPLIED INTELLIGENCE
ISSN	0924-669X
卷号	49 期号:5 页码:1925-1936
摘要	The Restricted Boltzmann machine (RBM) has been proven to be a powerful tool in many specific applications, such as representational learning, document modeling, and many other learning tasks. However, the extensions of the RBM are rarely used in the field of multi-view learning. In this paper, we present a new RBM model based on canonical correlation analysis, named as the correlation RBM, for multi-view learning. The correlation RBM computes multiple representations by regularizing the marginal likelihood function with the consistency among representations from different views. In addition, the multimodal deep model can obtain a unified representation that fuses multiple representations together. Therefore, we stack the correlation RBM to create the correlation deep belief network (DBN), and then propose the multimodal correlation DBN for learning multi-view data representations. Contrasting with existing multi-view classification methods, such as multi-view Gaussian process with posterior consistency (MvGP) and consensus and complementarity based maximum entropy discrimination (MED-2C), the correlation RBM and the multimodal correlation DBN have achieved satisfactory results on two-class and multi-class classification datasets. Experimental results show that correlation RBM and the multimodal correlation DBN are effective learning algorithms.
关键词	Restricted boltzmann machines Deep belief networks Multi-view learning Canonical correlation analysis Multimodal learning
DOI	10.1007/s10489-018-1379-8
收录类别	SCI
语种	英语
资助项目	Fundamental Research Funds for the Central Universities[2017XKZD03]
WOS研究方向	Computer Science
WOS类目	Computer Science, Artificial Intelligence
WOS记录号	WOS:000463843400017
出版者	SPRINGER
引用统计	被引频次：14[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/4282
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Ding, Shifei
作者单位	1.China Univ Min & Technol, Sch Comp Sci & Technol, Xuzhou 221116, Jiangsu, Peoples R China 2.Chinese Acad Sci, Key Lab Intelligent Informat Proc, Inst Comp Technol, Beijing 100190, Peoples R China 3.Shandong Normal Univ, Sch Informat Sci & Engn, Jinan 250358, Shandong, Peoples R China
推荐引用方式 GB/T 7714	Zhang, Nan,Ding, Shifei,Liao, Hongmei,et al. Multimodal correlation deep belief networks for multi-view classification[J]. APPLIED INTELLIGENCE,2019,49(5):1925-1936.
APA	Zhang, Nan,Ding, Shifei,Liao, Hongmei,&Jia, Weikuan.(2019).Multimodal correlation deep belief networks for multi-view classification.APPLIED INTELLIGENCE,49(5),1925-1936.
MLA	Zhang, Nan,et al."Multimodal correlation deep belief networks for multi-view classification".APPLIED INTELLIGENCE 49.5(2019):1925-1936.