Multimodal correlation deep belief networks for multi-view classification
文献类型：期刊论文
| 作者 | Liao, Hongmei3; Jia, Weikuan1; Zhang, Nan3; Ding, Shifei2,3 |
| 刊名 | APPLIED INTELLIGENCE
 |
| 出版日期 | 2019-05-01 |
| 卷号 | 49期号:5页码:1925-1936 |
| 关键词 | Restricted boltzmann machines Deep belief networks Multi-view learning Canonical correlation analysis Multimodal learning |
| ISSN号 | 0924-669X |
| DOI | 10.1007/s10489-018-1379-8 |
| 英文摘要 | 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. |
| 资助项目 | Fundamental Research Funds for the Central Universities[2017XKZD03] |
| WOS研究方向 | Computer Science |
| 语种 | 英语 |
| WOS记录号 | WOS:000463843400017 |
| 出版者 | SPRINGER |
| 源URL | [http://119.78.100.204/handle/2XEOYT63/4281]  |
| 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.Shandong Normal Univ, Sch Informat Sci & Engn, Jinan 250358, Shandong, Peoples R China 2.Chinese Acad Sci, Key Lab Intelligent Informat Proc, Inst Comp Technol, Beijing 100190, Peoples R China 3.China Univ Min & Technol, Sch Comp Sci & Technol, Xuzhou 221116, Jiangsu, Peoples R China |
| 推荐引用方式 GB/T 7714 | Liao, Hongmei,Jia, Weikuan,Zhang, Nan,et al. Multimodal correlation deep belief networks for multi-view classification[J]. APPLIED INTELLIGENCE,2019,49(5):1925-1936. |
| APA | Liao, Hongmei,Jia, Weikuan,Zhang, Nan,&Ding, Shifei.(2019).Multimodal correlation deep belief networks for multi-view classification.APPLIED INTELLIGENCE,49(5),1925-1936. |
| MLA | Liao, Hongmei,et al."Multimodal correlation deep belief networks for multi-view classification".APPLIED INTELLIGENCE 49.5(2019):1925-1936. |
入库方式： OAI收割
来源：计算技术研究所
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