.png){kind=icon}
返回
A new multi-view learning machine with incomplete data
.png){kind=icon}
PRE
AI
DOI：10.1007/s10044-020-00863-y.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Multi-view learning with incomplete views (MVL-IV) is a reliable algorithm to process incomplete datasets which consist of instances with missing views or features. In MVL-IV, it exploits the connections among multiple views and suggests that different views are generated from a shared subspace such that it can recover the missing views or features well while MVL-IV neglects two facts. One is that different views should always be generated from different subspaces. The other is that the information of view-based classifiers is useful to the design of MVL-IV. Thus, on the base of MVL-IV, we consider these two facts and develop a new multi-view learning with incomplete data (NMVL-IV). Related experiments on clustering, regression, classification, bipartite ranking, and image retrieval have validated that the proposed NMVL-IV can recover the incomplete data much better.
Keyword:
Multi-view learning
Incomplete data
Low-rank assumption
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
2
论文数:
2.0K
被引数:
1.9K
机构
引用论文
A novel formulation of orthogonal polynomial kernel functions for SVM classifiers: The Gegenbauer family.png)
PATTERN RECOGNITION
PATTERN RECOGNITIONIF7.6
PREAI
分享收藏Arsenic removal from aqueous solutions by adsorption using novel MIL-53(Fe) as a highly efficient adsorbent使用新型MIL-53(Fe) 作为高效吸附剂通过吸附从水溶液中去除砷RSC Advances
RSC AdvancesIF0
PREAI
分享收藏A Reconstruction Error Based Framework for Multi-Label and Multi-View Learning基于重构误差的多标签多视图学习框架
PREAI
分享收藏Globalized and localized canonical correlation analysis with multiple empirical kernel mapping具有多重经验核映射的全球化和本地化典型相关分析NEUROCOMPUTING
NEUROCOMPUTINGIF6.5
PREAI
分享收藏
查看更多内容