Deep Active Learning over the Long Tail

Yonatan Geifman
Yonatan Geifman

arXiv: Learning, Volume abs/1711.00941, 2017.

Cited by: 20|Bibtex|Views12
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Other Links: dblp.uni-trier.de|academic.microsoft.com|arxiv.org

Abstract:

This paper is concerned with pool-based active learning for deep neural networks. Motivated by coreset dataset compression ideas, we present a novel active learning algorithm that queries consecutive points from the pool using farthest-first traversals in the space of neural activation over a representation layer. We show consistent and o...More

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