Gao, J. B.; Gunn, S. R.; Harris, C. J. Mean field method for the support vector machine regression. (English) Zbl 1006.68818 Neurocomputing 50, 391-405 (2003). Summary: This paper deals with two subjects. First, we will show how support vector machine (SVM) regression problem can be solved as the maximum a posteriori prediction in the Bayesian framework. The second part describes an approximation technique that is useful in performing calculations for SVMs based on the mean field algorithm which was originally proposed in Statistical Physics of disordered systems. One advantage is that it handle posterior averages for Gaussian process which are not analytically tractable. Cited in 1 Document MSC: 68U99 Computing methodologies and applications 68T05 Learning and adaptive systems in artificial intelligence Keywords:support vector machine; mean field method; regression; Gaussian process Software:LOQO; SVMlight PDFBibTeX XMLCite \textit{J. B. Gao} et al., Neurocomputing 50, 391--405 (2003; Zbl 1006.68818) Full Text: DOI