A PAC-Bayes approach to the Set Covering Machine

Laviolette, François, Marchand, Mario, Shah, Mohak

Neural Information Processing Systems 

We design a new learning algorithm for the Set Covering Machine from a PAC-Bayes perspective and propose a PAC-Bayes risk bound which is minimized for classifiers achieving a non trivial margin-sparsity tradeoff.

Similar Docs  Excel Report  more

TitleSimilaritySource
None found