Skip to main content
Article thumbnail
Location of Repository

Online relative margin maximization for statistical machine translation

By Vladimir Eidelman, Yuval Marton and Philip Resnik

Abstract

Recent advances in large-margin learning have shown that better generalization can be achieved by incorporating higher order information into the optimization, such as the spread of the data. However, these so-lutions are impractical in complex struc-tured prediction problems such as statis-tical machine translation. We present an online gradient-based algorithm for rela-tive margin maximization, which bounds the spread of the projected data while max-imizing the margin. We evaluate our op-timizer on Chinese-English and Arabic-English translation tasks, each with small and large feature sets, and show that our learner is able to achieve significant im-provements of 1.2-2 BLEU and 1.7-4.3 TER on average over state-of-the-art opti-mizers with the large feature set.

Year: 2013
OAI identifier: oai:CiteSeerX.psu:10.1.1.641.5080
Provided by: CiteSeerX
Download PDF:
Sorry, we are unable to provide the full text but you may find it at the following location(s):
  • http://www.umiacs.umd.edu/~vla... (external link)
  • http://www.umiacs.umd.edu/~vla... (external link)
  • http://citeseerx.ist.psu.edu/v... (external link)
  • Suggested articles


    To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.