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 classification using 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.
Neural Information Processing Systems
Dec-31-2004