中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
A Scalable Kernel-Based Semisupervised Metric Learning Algorithm with Out-of-Sample Generalization Ability

文献类型:期刊论文

作者Yeung, Dit-Yan1; Chang, Hong2; Dai, Guang1
刊名NEURAL COMPUTATION
出版日期2008-11-01
卷号20期号:11页码:2839-2861
ISSN号0899-7667
英文摘要In recent years, metric learning in the semisupervised setting has aroused a lot of research interest. One type of semisupervised metric learning utilizes supervisory information in the form of pairwise similarity or dissimilarity constraints. However, most methods proposed so far are either limited to linear metric teaming or unable to scale well with the data set size. In this letter, we propose a nonlinear metric learning method based on the kernel approach.-By applying low-rank approximation to the kernel matrix, our method can handle significantly larger data sets. Moreover, our low-rank approximation scheme can naturally lead to out-of-sample generalization. Experiments performed on both artificial and real-world data show very promising results.
资助项目Council of the Hong Kong Special Administrative Region, China[621706]
WOS研究方向Computer Science
语种英语
WOS记录号WOS:000260113500010
出版者M I T PRESS
源URL[http://119.78.100.204/handle/2XEOYT63/11151]  
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Yeung, Dit-Yan
作者单位1.Hong Kong Univ Sci & Technol, Dept Comp Sci & Engn, Hong Kong, Hong Kong, Peoples R China
2.Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing 100190, Peoples R China
推荐引用方式
GB/T 7714
Yeung, Dit-Yan,Chang, Hong,Dai, Guang. A Scalable Kernel-Based Semisupervised Metric Learning Algorithm with Out-of-Sample Generalization Ability[J]. NEURAL COMPUTATION,2008,20(11):2839-2861.
APA Yeung, Dit-Yan,Chang, Hong,&Dai, Guang.(2008).A Scalable Kernel-Based Semisupervised Metric Learning Algorithm with Out-of-Sample Generalization Ability.NEURAL COMPUTATION,20(11),2839-2861.
MLA Yeung, Dit-Yan,et al."A Scalable Kernel-Based Semisupervised Metric Learning Algorithm with Out-of-Sample Generalization Ability".NEURAL COMPUTATION 20.11(2008):2839-2861.

入库方式: OAI收割

来源:计算技术研究所

浏览0
下载0
收藏0
其他版本

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。