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标架型RKHS中的SVM的半参数估计 被引量：1

Semiparametric estimation of SVM in frameable RKHS
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摘要 在基于标架型的再生核希尔伯特空间中,研究了SVM算法下,解的对偶形式和原形式之间的关系,进而将SVM算法与最小二乘法相结合,讨论了支持向量机的半参数估计. Relationship between the dual form and primal form of solution based on SVM method in a frameable reproducing kernel Hilbert space is studied. Furthermore, by combining SVM method with least squares method, semiparametric estimation of SVM is discussed.
作者 周德强
机构地区 长江大学信息与数学学院
出处 《浙江大学学报（理学版）》 CAS CSCD 北大核心 2008年第2期150-152,159,共4页 Journal of Zhejiang University（Science Edition）
关键词 支持向量机 再生核希尔伯特空间 半参数估计 support vector machines reproducing kernel Hilbert space semiparametric estimation
分类号 TP391 [自动化与计算机技术—计算机应用技术]
  • 相关文献

参考文献8

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共引文献60

同被引文献11

  • 1Fan Jianping,Luo Hangzai,Li Xiaodong.Semantic VideoClassification by Integrating Flexible Mixture Model withAdaptive EM Algorithm[C]//Proc.of the 5th ACM SIGMMInternational Workshop on Multimedia Information Retrieval.New York,USA:ACM Press,2003.
  • 2Cohen D A,Ghahramani Z,Jordan M I.Active Learning withStatistical Model[J].Journal of Artificial Intelligence Research,1996,4(1):129-145.
  • 3Natsev A P,Naphade M R,Tesic J.Learning the Semantics ofMultimedia Queries and Concepts from a Small Number ofExamples[C]//Proc.of the 13th Annual ACM InternationalConference on Multimedia.New York,USA:ACM Press,2005.
  • 4Snoek C G M,Worring M,Gemert J C V.The ChallengeProblem for Automated Detection of 101 Semantic Conceptsin Multimedia[C]//Proc.of the 14th Annual ACM InternationalConference on Multimedia.New York,USA:ACM Press,2006.
  • 5Yang Jun,Yan Rong,Hauptmann A.Cross-domain VideoConcept Detection Using Adaptive SVMs[C]//Proc.of the15th International Conference on Multimedia.New York,USA:ACM Press,2007.
  • 6Huang Teming,Kecman V,Kopriva L.Kernel Based Algo-rithms for Mining Huge Data Sets:Supervised,Semi-Supervised,and Unsupervised Learning[M].Berlin,Germany:Springer-Verlag,2010.
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  • 8Zhu Xiaojin,Ghahramani Z,Lafferty J.Semi-supervisedLearning Using Gaussian Fields and Harmonic Functions[C]//Proc.of the 20th International Conference on MachineLearning.Washington D.C.,USA:[s.n.],2003.
  • 9Simon T,Edward C.Support Vector Machine Active Learningfor Image Retrieval[C]//Proc.of the 9th ACM InternationalConference on Multimedia.New York,USA:ACM Press,2001.
  • 10Wang Lei,Kap L C,Zhang Zhihua.Bootstrapping SVM ActiveLearning by Incorporating Unlabelled Image for ImageRetrieval[C]//Proc.of IEEE Computer Society Conference onComputer Vision and Pattern Recognition.Washington D.C.,USA:IEEE Computer Society,2003.

引证文献1

二级引证文献3

浙江大学学报（理学版）
2008年 第2期

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