OPT OpenIR  > 光学影像学习与分析中心
Semisupervised Learning With Parameter-Free Similarity of Label and Side Information
Zhang, Rui1; Nie, Feiping1; Li, Xuelong2
Department光学影像学习与分析中心
2019-02
Source PublicationIEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
ISSN2162-237X;2162-2388
Volume30Issue:2Pages:405–414
Contribution Rank2
Abstract

As for semisupervised learning, both label information and side information serve as pivotal indicators for the classification. Nonetheless, most of related research works utilize either label information or side information instead of exploiting both of them simultaneously. To address the referred defect, we propose a graph-based semisupervised learning (GSL) problem according to both given label information and side information. To solve the GSL problem efficiently, two novel self-weighted strategies are proposed based on solving associated equivalent counterparts of a GSL problem, which can be widely applied to a spectrum of biobjective optimizations. Different from a conventional technique to amalgamate must-link and cannotlink into a single similarity for convenient optimization, we derive a new parameter-free similarity, upon which intrinsic graph and penalty graph can be separately developed. Consequently, a novel semisupervised classification algorithm can be summarized correspondingly with a theoretical analysis.

KeywordGraph-based semisupervised learning (GSL) quadratic trace ratio (QTR) problem side information soft label
DOI10.1109/TNNLS.2018.2843798
Indexed BySCI
Language英语
WOS IDWOS:000457114600007
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Citation statistics
Document Type期刊论文
Identifierhttp://ir.opt.ac.cn/handle/181661/31195
Collection光学影像学习与分析中心
Corresponding AuthorNie, Feiping
Affiliation1.Northwestern Polytech Univ, Ctr OPT IMagery Anal & Learning, Sch Comp Sci, Xian 710072, Shaanxi, Peoples R China
2.Chinese Acad Sci, State Key Lab Transient Opt & Photon, Ctr OPT IMagery Anal & Learning, Xian Inst Opt & Precis Mech, Xian 710119, Shaanxi, Peoples R China
Recommended Citation
GB/T 7714
Zhang, Rui,Nie, Feiping,Li, Xuelong. Semisupervised Learning With Parameter-Free Similarity of Label and Side Information[J]. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,2019,30(2):405–414.
APA Zhang, Rui,Nie, Feiping,&Li, Xuelong.(2019).Semisupervised Learning With Parameter-Free Similarity of Label and Side Information.IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,30(2),405–414.
MLA Zhang, Rui,et al."Semisupervised Learning With Parameter-Free Similarity of Label and Side Information".IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 30.2(2019):405–414.
Files in This Item:
File Name/Size DocType Version Access License
Semisupervised Learn(1215KB)期刊论文出版稿开放获取CC BY-NC-SAView Application Full Text
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Zhang, Rui]'s Articles
[Nie, Feiping]'s Articles
[Li, Xuelong]'s Articles
Baidu academic
Similar articles in Baidu academic
[Zhang, Rui]'s Articles
[Nie, Feiping]'s Articles
[Li, Xuelong]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Zhang, Rui]'s Articles
[Nie, Feiping]'s Articles
[Li, Xuelong]'s Articles
Terms of Use
No data!
Social Bookmark/Share
File name: Semisupervised Learning With Parameter-Free Similarity of Label and Side Information.pdf
Format: Adobe PDF
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.