Hybrid structure for robust dimensionality reduction

CORC > 西安光学精密机械研究所 > 中国科学院西安光学精密机械研究所 > 光学影像学习与分析中心

	Hybrid structure for robust dimensionality reduction
	Lu, Xiaoqiang; Yuan, Yuan
刊名	neurocomputing
	2014-01-26
卷号	124 期号:si 页码:131-138
关键词	Dimensionality reduction Pattern recognition Manifold learning Unsupervised learning Face recognition
ISSN号	0925-2312
英文摘要	in recent years, dimensionality reduction has attracted a great deal of attention in the communities of machine learning and data mining. the basic goal of dimensionality reduction is to discover the low dimensional manifold embedded in a high dimensional space. although some existing manifold learning algorithms (isomap, le, lle, ltsa, etc.) can capture the local structure of data manifold, they have poor performance in some recognition tasks. this is mainly because that they cannot handle well with the "out of sample" problem. moreover, these algorithms are sensitive to the choice of nearest neighbors, which is crucial in classification. to address these problems, this paper proposes a robust dimensionality reduction algorithm with local and global structure (rlgs) based on a novel adaptive weighting mechanism. hybrid structure of local and global structures is studied. by using the adaptive weight, rlgs has the capacity of adaptively exploiting non-linear structure of data manifold and is robust to parameters. experiments demonstrate that rlgs performs better on public face databases compared with other reported algorithms. (c) 2013 elsevier b.v. all rights reserved.
WOS标题词	science & technology ; technology
类目[WOS]	computer science, artificial intelligence
研究领域[WOS]	computer science
关键词[WOS]	tangent-space alignment ; face-recognition ; framework
收录类别	SCI ; EI
语种	英语
WOS记录号	WOS:000326853600016
公开日期	2015-03-18
内容类型	期刊论文
源URL	[http://ir.opt.ac.cn/handle/181661/22395]
专题	西安光学精密机械研究所_光学影像学习与分析中心
作者单位	Chinese Acad Sci, Xian Inst Opt & Precis Mech, State Key Lab Transient Opt & Photon, Ctr OPT IMagery Anal & Learning OPTIMAL, Xian 710119, Shaanxi, Peoples R China
推荐引用方式 GB/T 7714	Lu, Xiaoqiang,Yuan, Yuan. Hybrid structure for robust dimensionality reduction[J]. neurocomputing,2014,124(si):131-138.
APA	Lu, Xiaoqiang,&Yuan, Yuan.(2014).Hybrid structure for robust dimensionality reduction.neurocomputing,124(si),131-138.
MLA	Lu, Xiaoqiang,et al."Hybrid structure for robust dimensionality reduction".neurocomputing 124.si(2014):131-138.