SELM: Semi-supervised ELM with application in sparse calibrated location estimation

doi:10.1016/j.neucom.2010.12.043

	SELM: Semi-supervised ELM with application in sparse calibrated location estimation
	Liu, Junfa 1; Chen, Yiqiang 1; Liu, Mingjie 1,2; Zhao, Zhongtang 1,2
	2011-09-01
发表期刊	NEUROCOMPUTING
ISSN	0925-2312
卷号	74 期号:16 页码:2566-2572
摘要	Indoor location estimation based on Wi-Fi has attracted more and more attention from both research and industry fields. It brings two significant challenges. One is requiring a vast amount of labeled calibration data. The other is real-time training and testing for location estimation task. Traditional machine learning methods cannot get high performance in both aspects. This paper proposed a novel semi-supervised learning method SELM (semi-supervised extreme learning machine) and applied it to sparse calibrated location estimation. There are two advantages of the proposed SELM. First, it employs graph Laplacian regularization to import large number of unlabeled samples which can dramatically reduce labeled calibration samples. Second, it inherits the good property of ELM on extreme training and testing speed. Comparative experiments show that with same number of labeled samples, our method outperforms original ELM and back propagation (BP) network, especially in the case that the calibration data is very sparse. (C) 2011 Elsevier B.V. All rights reserved.
关键词	Semi-supervised extreme learning machine Location estimation Sparse calibration Graph Laplacian
DOI	10.1016/j.neucom.2010.12.043
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[90820303] ; National Natural Science Foundation of China[61070110] ; National 863 High Technology Research and Development Program of China[2009AA01Z320] ; Beijing Municipal Education Commission
WOS研究方向	Computer Science
WOS类目	Computer Science, Artificial Intelligence
WOS记录号	WOS:000295106000019
出版者	ELSEVIER SCIENCE BV
引用统计	被引频次：71[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/2XEOYT63/13169
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Liu, Junfa
作者单位	1.Chinese Acad Sci, Inst Comp Technol, Beijing 100190, Peoples R China 2.Chinese Acad Sci, Grad Sch, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Liu, Junfa,Chen, Yiqiang,Liu, Mingjie,et al. SELM: Semi-supervised ELM with application in sparse calibrated location estimation[J]. NEUROCOMPUTING,2011,74(16):2566-2572.
APA	Liu, Junfa,Chen, Yiqiang,Liu, Mingjie,&Zhao, Zhongtang.(2011).SELM: Semi-supervised ELM with application in sparse calibrated location estimation.NEUROCOMPUTING,74(16),2566-2572.
MLA	Liu, Junfa,et al."SELM: Semi-supervised ELM with application in sparse calibrated location estimation".NEUROCOMPUTING 74.16(2011):2566-2572.