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Minimum-Margin Active Learning

Published in arXiv (Cornell University) • May 31, 2019
NobleIDNI2P18W25R95S81
Authors:
Heinrich Jiang
,
Maya R. Gupta

Abstract

We present a new active sampling method we call min-margin which trains multiple learners on bootstrap samples and then chooses the examples to label based on the candidates' minimum margin amongst the bootstrapped models. This extends standard margin sampling in a way that increases its diversity i...

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