( Och and Ney , 2002 ; Blunsom et al. , 2008 ) used maximum likelihood estimation to learn weights for MT. ( Och , 2003 ; Moore and Quirk , 2008 ; Zhao and Chen , 2009 ; Galley and Quirk , 2011 ) employed an evaluation metric as a loss function and directly optimized it .
optimal search for minimum error rate training
Michel Galley Chris Quirk
Several works have proposed discriminative techniques to train log-linear model for SMT . ( Och and Ney , 2002 ; Blunsom et al. , 2008 ) used maximum likelihood estimation to learn weights for MT. ( Och , 2003 ; Moore and Quirk , 2008 ; Zhao and Chen , 2009 ; Galley and Quirk , 2011 ) employed an evaluation metric as a loss function and directly optimized it . ( Watanabe et al. , 2007 ; Chiang et al. , 2008 ; Hopkins and May , 2011 ) proposed other optimization objectives by introducing a margin-based and ranking-based indirect loss functions .
( Och and Ney , 2002 ; Blunsom et al. , 2008 ) used maximum likelihood estimation to learn weights for MT. ( Och , 2003 ; Moore and Quirk , 2008 ; Zhao and Chen , 2009 ; @@CITATION ) employed an evaluation metric as a loss function and directly optimized it .