1. A method for active learning using privileged information, the method comprising: receiving, by a processing device, a set of labeled examples and a set of unlabeled examples; for each unlabeled example in the set of unlabeled examples, determining, using the processing device, whether to query at least one of an oracle to obtain a label for the unlabeled example or a teacher to obtain privileged information about the unlabeled example; and outputting, using the processing device, a decision rule based on minimizing a number of queries to the oracle for a label and the teacher for privileged information, wherein minimizing the number of queries to the teacher and the oracle is based on a cost of querying the teacher or the oracle.
1. A method for active learning using privileged information, the method comprising: receiving, by a processing device, a set of labeled examples and a set of unlabeled examples; for each unlabeled example in the set of unlabeled examples, determining, using the processing device, whether to query at least one of an oracle to obtain a label for the unlabeled example or a teacher to obtain privileged information about the unlabeled example; and outputting, using the processing device, a decision rule based on minimizing a number of queries to the oracle for a label and the teacher for privileged information, wherein minimizing the number of queries to the teacher and the oracle is based on a cost of querying the teacher or the oracle. 18. The method of claim 1 , wherein the teacher comprises a plurality of sub-teachers, the method further comprising: clustering labeled examples in the set of labeled examples into a plurality of clusters; ranking sub-teachers based on a measure of utility of privileged information for each of the clusters of labeled examples; assigning unlabeled examples to the clusters obtained using the set of labeled examples; and prioritizing acquisition of privileged information based on a ranking of the sub-teachers based on a cluster providing the closest to an example selected from the set of unlabeled examples.