Supervised Gaussian Process Latent Variable Model for 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

	Supervised Gaussian Process Latent Variable Model for Dimensionality Reduction
	Gao, Xinbo 1; Wang, Xiumei 1; Tao, Dacheng 2; Li, Xuelong 3
刊名	ieee transactions on systems man and cybernetics part b-cybernetics
	2011-04-01
卷号	41 期号:2 页码:425-434
关键词	Dimensionality reduction Gaussian process latent variable model (GP-LVM) generalized discriminant analysis (GDA) probabilistic principal component analysis (probabilistic PCA) supervised learning
ISSN号	1083-4419
通讯作者	x. gao
合作状况	其它
英文摘要	the gaussian process latent variable model (gp-lvm) has been identified to be an effective probabilistic approach for dimensionality reduction because it can obtain a low-dimensional manifold of a data set in an unsupervised fashion. consequently, the gp-lvm is insufficient for supervised learning tasks (e. g., classification and regression) because it ignores the class label information for dimensionality reduction. in this paper, a supervised gp-lvm is developed for supervised learning tasks, and the maximum a posteriori algorithm is introduced to estimate positions of all samples in the latent variable space. we present experimental evidences suggesting that the supervised gp-lvm is able to use the class label information effectively, and thus, it outperforms the gp-lvm and the discriminative extension of the gp-lvm consistently. the comparison with some supervised classification methods, such as gaussian process classification and support vector machines, is also given to illustrate the advantage of the proposed method.
学科主题	信号与模式识别 ; 计算机应用其他学科（含图像处理）
WOS标题词	science & technology ; technology
类目[WOS]	automation & control systems ; computer science, artificial intelligence ; computer science, cybernetics
研究领域[WOS]	automation & control systems ; computer science
关键词[WOS]	principal component analysis ; classification ; recognition
收录类别	SCI ; EI
语种	英语
WOS记录号	WOS:000288454300009
公开日期	2011-01-12
内容类型	期刊论文
源URL	[http://ir.opt.ac.cn/handle/181661/8628]
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	1.Xidian Univ, Sch Elect Engn, Xian 710071, Peoples R China 2.Nanyang Technol Univ, Sch Comp Engn, Singapore 639798, Singapore 3.Chinese Acad Sci, Ctr OPT IMagery Anal & Learning OPTIMAL, State Key Lab Transient Opt & Photon, Xian Inst Opt & Precis Mech, Xian 710119, Peoples R China
推荐引用方式 GB/T 7714	Gao, Xinbo,Wang, Xiumei,Tao, Dacheng,et al. Supervised Gaussian Process Latent Variable Model for Dimensionality Reduction[J]. ieee transactions on systems man and cybernetics part b-cybernetics,2011,41(2):425-434.
APA	Gao, Xinbo,Wang, Xiumei,Tao, Dacheng,&Li, Xuelong.(2011).Supervised Gaussian Process Latent Variable Model for Dimensionality Reduction.ieee transactions on systems man and cybernetics part b-cybernetics,41(2),425-434.
MLA	Gao, Xinbo,et al."Supervised Gaussian Process Latent Variable Model for Dimensionality Reduction".ieee transactions on systems man and cybernetics part b-cybernetics 41.2(2011):425-434.