2004 RecentAdvInBayesianInf

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Subject Headings: Bayesian Inference Algorithm, Variance Inference Algorithm, Relevance Vector Machine, Support Vector Machine.



Relevance Vector Machine (Tipping, 1999)

  • Bayesian alternative to support vector machine (SVM)
  • Limitations of the SVM:

– two classes – large number of kernels (in spite of sparsity) – kernels must satisfy Mercer criterion – cross-validation to set parameters C (and ε) – decisions at outputs instead of probabilities

Properties – comparable error rates to SVM on new data – no cross-validation to set comlexity parameters – applicable to wide choice of basis function – multi-class classification – probabilistic outputs – dramatically fewer kernels (by an order of magnitude) – but, slower to train than SVM,

 AuthorvolumeDate ValuetitletypejournaltitleUrldoinoteyear
2004 RecentAdvInBayesianInfChristopher M. BishopRecent Advances in Bayesian Inference Techniqueshttp://www.siam.org/meetings/sdm04/files/Keynote Bishop.pdf