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22
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ICML
2005
IEEE
87
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Machine Learning
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ICML 2005
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PAC-Bayes risk bounds for sample-compressed Gibbs classifiers
15 years 1 months ago
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www.machinelearning.org
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
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