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Machine Learning

There are various ways in which the large number of parameters contained in statistical machine translation models may be acquired. While early work emphasized the use of generative statistical models and methods such as the expectation maximization (EM) algorithm, the use of alternative machine learning paradigms such as discriminative training has been explored.

Machine Learning and its 9 sub-topics are the main subject of 548 publications.

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  • Riezler et al. (2014)
  • Ni et al. (2010)
  • Wang and Shawe-Taylor (2010)
  • Ambati et al. (2011)
  • Guzman and Vogel (2012)
  • Saluja et al. (2012)
  • Lee and Rim (2012)
  • Liu et al. (2012)
  • Kolachina et al. (2012)
  • Chung and Galley (2012)
  • Eidelman (2012)
  • Cohn et al. (2009)
  • Haffari et al. (2009)
  • Kääriäinen (2009)
  • Zhang and Li (2009)
  • Deselaers et al. (2009)
  • Hayashi et al. (2009)
  • Haffari and Sarkar (2009)
  • Ananthakrishnan et al. (2010)
  • Ambati and Carbonell (2009)
  • Bloodgood and Callison-Burch (2010)
  • DeNero and Klein (2010)
  • Yamada et al. (2003)
  • Ananthakrishnan et al. (2010)
  • Brown (2010)
  • Srivastava et al. (2011)
  • Li et al. (2010)
  • Blunsom and Cohn (2010)
  • Bellare et al. (2009)
  • Xiang and Ittycheriah (2011)

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