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96
Voted
ICML
2007
IEEE
16 years 2 months ago
Sample compression bounds for decision trees
We propose a formulation of the Decision Tree learning algorithm in the Compression settings and derive tight generalization error bounds. In particular, we propose Sample Compres...
Mohak Shah
79
Voted
ICML
2005
IEEE
16 years 2 months ago
PAC-Bayes risk bounds for sample-compressed Gibbs classifiers
We extend the PAC-Bayes theorem to the sample-compression setting where each classifier is represented by two independent sources of information: a compression set which consists ...
François Laviolette, Mario Marchand