Title: Picking groups instead of samples: A close look at Static Pool-based Meta-Active Learning
Abstract: Active Learning techniques are used to tackle learning problems where obtaining training labels is costly. In this work we use Meta-Active Learning to learn to select a subset of samples from a pool of unsupervised input for further annotation. This scenario is called Static Pool-based Meta- Active Learning. We propose to extend existing approaches by performing the selection in a manner that, unlike previous works, can handle the selection of each sample based on the whole selected subset.
Publication Year: 2019
Publication Date: 2019-11-01
Language: en
Type: preprint
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Cited By Count: 1
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