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The cross entropy method for classification
2005
Proceedings of the 22nd international conference on Machine learning - ICML '05
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We consider support vector machines for binary classification. As opposed to most approaches we use the number of support vectors (the "L 0 norm") as a regularizing term instead of the L 1 or L 2 norms. In order to solve the optimization problem we use the cross entropy method to search over the possible sets of support vectors. The algorithm consists of solving a sequence of efficient linear programs. We report experiments where our method produces generalization errors that are similar to
doi:10.1145/1102351.1102422
dblp:conf/icml/MannorPR05
fatcat:adjeehb7sja5vnwngurywaoqwm