Poelitz/2013b: Cross Domain Active Learning

Bibtype Proceedings
Bibkey Poelitz/2013b
Ls8autor Pölitz, Christian
Editor LWA
Title Cross Domain Active Learning
Publisher University of Bamberg
Abstract In this paper, we propose a solution to re-
duce the labeling costs by applying do-
main adaption methods coupled with ac-
tive learning to reduce the number labels
needed to train a classifier. We assume to
have only one task but different domains
in the sense that we have texts that come
from different distributions. Our approach
uses multi domain learning together with
active learning to find a minimum number
of texts to label from as few domains as
possible to train a classifier with a certain
confidence in its predictions.
Month Oktober
Year 2013
Projekt Kobra

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