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We consider the problem of noisy Bayesian active learning where we are given a finite set of functions $\mathcal {H}$ , a sample space $\mathcal {X}$ , and a label set $\mathcal {L}$ . One of the functions in $\mathcal {H}$ assigns labels to samples in $\mathcal {X}$ . The goal is to identify the function that generates the labels even though the result of a label query on a sample is corrupted...
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