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On the Theory of Learnining with Privileged Information
Dmitry Pechyony · Vladimir Vapnik

Mon Dec 06 12:00 AM -- 12:00 AM (PST) @

In Learning Using Privileged Information (LUPI) paradigm, along with the standard training data in the decision space, a teacher supplies a learner with the privileged information in the correcting space. The goal of the learner is to find a classifier with a low generalization error in the decision space. We consider a new version of empirical risk minimization algorithm, called Privileged ERM, that takes into account the privileged information in order to find a good function in the decision space. We outline the conditions on the correcting space that, if satisfied, allow Privileged ERM to have much faster learning rate in the decision space than the one of the regular empirical risk minimization.

Author Information

Dmitry Pechyony (NEC Labs)
Vladimir Vapnik