Web: http://arxiv.org/abs/2106.12059

Jan. 31, 2022, 2:11 a.m. | Andreas Kirsch, Sebastian Farquhar, Parmida Atighehchian, Andrew Jesson, Frederic Branchaud-Charron, Yarin Gal

cs.LG updates on arXiv.org arxiv.org

We provide a stochastic strategy for adapting well-known acquisition
functions to allow batch active learning. In deep active learning, labels are
often acquired in batches for efficiency. However, many acquisition functions
are designed for single-sample acquisition and fail when naively used to
construct batches. In contrast, state-of-the-art batch acquisition functions
are costly to compute. We show how to extend single-sample acquisition
functions to the batch setting. Instead of acquiring the top-K points from the
pool set, we account for the …

acquisition active learning arxiv deep learning stochastic

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