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Some marginal learning algorithms for unsupervised problems
Tao, Q; Wu, GW; Wang, FY; Wang, J
2005
发表期刊INTELLIGENCE AND SECURITY INFORMATICS, PROCEEDINGS
ISSN0302-9743
卷号3495页码:395-401
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.
收录类别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
出版者SPRINGER-VERLAG BERLIN
引用统计
文献类型期刊论文
条目标识符http://119.78.100.204/handle/2XEOYT63/10067
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Tao, Q
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
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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.(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.
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