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Unified subspace learning for incomplete and unlabeled multi-view data
Yin, Qiyue; Wu, Shu; Wang, Liang
Source PublicationPATTERN RECOGNITION
2017-07-01
Volume67Issue:67Pages:313-327
SubtypeArticle
AbstractMulti-view data with each view corresponding to a type of feature set are common in real world. Usually, previous multi-view learning methods assume complete views. However, multi-view data are often incomplete, namely some samples have incomplete feature sets. Besides, most data are unlabeled due to a large cost of manual annotation, which makes learning of such data a challenging problem. In this paper, we propose a novel subspace learning framework for incomplete and unlabeled multi-view data. The model directly optimizes the class indicator matrix, which establishes a bridge for incomplete feature sets. Besides, feature selection is considered to deal with high dimensional and noisy features. Furthermore, the inter-view and intra-view data similarities are preserved to enhance the model. To these ends, an objective is developed along with an efficient optimization strategy. Finally, extensive experiments are conducted for multi-view clustering and cross-modal retrieval, achieving the state-of-the-art performance under various settings. (C) 2017 Elsevier Ltd. All rights reserved.
KeywordMulti-view Learning Subspace Learning Incomplete And Unlabeled Data Multi-view Clustering Cross-modal Retrieval
WOS HeadingsScience & Technology ; Technology
DOI10.1016/j.patcog.2017.01.035
Indexed BySCI
Language英语
Funding Organizationstate key development program(2016YFB1001000) ; National Natural Science Foundation of China(61403390 ; U1435221)
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS IDWOS:000399520700026
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/14541
Collection智能感知与计算研究中心
AffiliationChinese Acad Sci, Inst Automat, Ctr Res Intelligent Percept & Comp, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Yin, Qiyue,Wu, Shu,Wang, Liang. Unified subspace learning for incomplete and unlabeled multi-view data[J]. PATTERN RECOGNITION,2017,67(67):313-327.
APA Yin, Qiyue,Wu, Shu,&Wang, Liang.(2017).Unified subspace learning for incomplete and unlabeled multi-view data.PATTERN RECOGNITION,67(67),313-327.
MLA Yin, Qiyue,et al."Unified subspace learning for incomplete and unlabeled multi-view data".PATTERN RECOGNITION 67.67(2017):313-327.
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