Gaussian processes and SVM: Mean field results and leave-one-out

Opper, Manfred and Winther, Ole Gaussian processes and SVM: Mean field results and leave-one-out. IN: Advances in large margin classifiers. Smola, Alex J.; Bartlett, Peter; Schölkopf, Bernhard and Schuurmans, Dale (eds) Cambridge, US: MIT.


In this chapter, we elaborate on the well-known relationship between Gaussian processes (GP) and Support Vector Machines (SVM). Secondly, we present approximate solutions for two computational problems arising in GP and SVM. The first one is the calculation of the posterior mean for GP classifiers using a `naive' mean field approach. The second one is a leave-one-out estimator for the generalization error of SVM based on a linear response method. Simulation results on a benchmark dataset show similar performances for the GP mean field algorithm and the SVM algorithm. The approximate leave-one-out estimator is found to be in very good agreement with the exact leave-one-out error.

Divisions: ?? 13770100JJ ??
Additional Information: Massachusetts Institute of Technology Press (MIT Press) Available on Google Books
Uncontrolled Keywords: Gaussian processes,support vector machines



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