English

Frustratingly Easy Domain Adaptation

Machine Learning 2009-07-13 v1 Computation and Language

Abstract

We describe an approach to domain adaptation that is appropriate exactly in the case when one has enough ``target'' data to do slightly better than just using only ``source'' data. Our approach is incredibly simple, easy to implement as a preprocessing step (10 lines of Perl!) and outperforms state-of-the-art approaches on a range of datasets. Moreover, it is trivially extended to a multi-domain adaptation problem, where one has data from a variety of different domains.

Keywords

Cite

@article{arxiv.0907.1815,
  title  = {Frustratingly Easy Domain Adaptation},
  author = {Hal Daumé},
  journal= {arXiv preprint arXiv:0907.1815},
  year   = {2009}
}
R2 v1 2026-06-21T13:23:36.991Z