CASIA OpenIR  > 09年以前成果
Some marginal learning algorithms for unsupervised problems
Tao, Q; Wu, GW; Wang, FY; Wang, J; Kantor, P; Muresan, G; Roberts, F; Zeng, DD; Wang, FY; Chen, H; Merkle, RC
2005
发表期刊INTELLIGENCE AND SECURITY INFORMATICS, PROCEEDINGS
卷号3495页码:395-401
文章类型Article
摘要In this paper, we investigate one-class and clustering problems by using statistical learning theory. To establish a universal framework, a unsupervised learning problem with predefined threshold eta is formally described and the intuitive margin is introduced. Then, one-class and clustering problems are formulated as two specific eta-unsupervised problems. By defining a specific hypothesis space in eta-one-class problems, the crucial minimal sphere algorithm for regular one-class problems is proved to be a maximum margin algorithm. Furthermore, some new one-class and clustering marginal algorithms can be achieved in terms of different hypothesis spaces. Since the nature in SVMs is employed successfully, the proposed algorithms have robustness, flexibility and high performance. Since the parameters in SVMs are interpretable, our unsupervised learning framework is clear and natural. To verify the reasonability of our formulation, some synthetic and real experiments are conducted. They demonstrate that the proposed framework is not only of theoretical interest, but they also has a legitimate place in the family of practical unsupervised learning techniques.
WOS标题词Science & Technology ; Technology
关键词[WOS]SUPPORT
收录类别ISTP ; SCI
语种英语
WOS研究方向Computer Science
WOS类目Computer Science, Artificial Intelligence ; Computer Science, Information Systems ; Computer Science, Interdisciplinary Applications ; Computer Science, Theory & Methods
WOS记录号WOS:000230114100034
引用统计
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/9114
专题09年以前成果
作者单位1.Chinese Acad Sci, Inst Automat, Key Lab Complex Syst & Intelligence Sci, Beijing 100080, Peoples R China
2.Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligenct Informat Proc, Bioinformat Res Grp, Beijing 100080, Peoples R China
推荐引用方式
GB/T 7714
Tao, Q,Wu, GW,Wang, FY,et al. Some marginal learning algorithms for unsupervised problems[J]. INTELLIGENCE AND SECURITY INFORMATICS, PROCEEDINGS,2005,3495:395-401.
APA Tao, Q.,Wu, GW.,Wang, FY.,Wang, J.,Kantor, P.,...&Merkle, RC.(2005).Some marginal learning algorithms for unsupervised problems.INTELLIGENCE AND SECURITY INFORMATICS, PROCEEDINGS,3495,395-401.
MLA Tao, Q,et al."Some marginal learning algorithms for unsupervised problems".INTELLIGENCE AND SECURITY INFORMATICS, PROCEEDINGS 3495(2005):395-401.
条目包含的文件
条目无相关文件。
个性服务
推荐该条目
保存到收藏夹
查看访问统计
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Tao, Q]的文章
[Wu, GW]的文章
[Wang, FY]的文章
百度学术
百度学术中相似的文章
[Tao, Q]的文章
[Wu, GW]的文章
[Wang, FY]的文章
必应学术
必应学术中相似的文章
[Tao, Q]的文章
[Wu, GW]的文章
[Wang, FY]的文章
相关权益政策
暂无数据
收藏/分享
所有评论 (0)
暂无评论
 

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。