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On the Sample Complexity of Active Learning with Membership Queries

Wang, Ganghua et al.
arXiv (All) · Papers
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machine-learningstatistics-theory
This work revisits a fundamental question in active learning: how powerful is the ability to synthesize arbitrary queries? Compared to pool-based active learning, where the learner only selects queries from a given unlabeled pool, we find that this seemingly mild change in query ability may dramatic
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