Approximate Analytical Bootstrap Averages for Support Vector Classifiers

Malzahn, Dörthe, Opper, Manfred

Neural Information Processing Systems 

We compute approximate analytical bootstrap averages for support vector classificationusing a combination of the replica method of statistical physics and the TAP approach for approximate inference. We test our method on a few datasets and compare it with exact averages obtained by extensive Monte-Carlo sampling.

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