Active learning with confidence

Mark Dredze, Koby Crammer

Research output: Contribution to journalConference articlepeer-review

Abstract

Active learning is a machine learning approach to achieving high-accuracy with a small amount of labels by letting the learning algorithm choose instances to be labeled. Most of previous approaches based on discriminative learning use the margin for choosing instances. We present a method for incorporating confidence into the margin by using a newly introduced online learning algorithm and show empirically that confidence improves active learning.

Original languageEnglish (US)
Pages (from-to)233-236
Number of pages4
JournalProceedings of the Annual Meeting of the Association for Computational Linguistics
DOIs
StatePublished - 2008
Externally publishedYes
Event46th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, ACL 2008 - Columbus, United States
Duration: Jun 16 2008Jun 17 2008

ASJC Scopus subject areas

  • Computer Science Applications
  • Linguistics and Language
  • Language and Linguistics

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