D08-1050 from the packed chart , using a loglinear model to score the derivations
C04-1006 superior to the performance of the loglinear interpolation . In Table 4 ,
C04-1006 task , the improvement with the loglinear interpolation is statistically
D08-1076 , 2008 ) . Each system uses a loglinear combination of 20 to 30 feature
C04-1006 experiments , we investigated also the loglinear interpolation of the lexicon
C04-1006 propose and justify linear and loglinear interpolation methods . Statistical
C04-1006 significant at the 99 % level . For the loglinear interpo - lation , the target-to-source
C04-1006 Canadian Hansards task . Here , the loglinear interpolation performs best .
C04-1006 see that both the linear and the loglinear lexicon symmetrization methods
A00-2018 This is useful if one is using a loglinear model for smoothing . That is
C04-1168 in section 2 were used in the loglinear models . We did not perform parameter
C04-1006 article Model 6 is introduced as the loglinear interpolation of the other models
C04-1180 2004b ) parser , which uses a loglinear model of normal-form derivations
C04-1006 0:5 for both the linear and the loglinear interpolation , i.e. both translation
C04-1006 interpolation . Performing the loglinear interpolation , we observe a
C04-1006 one direction is large . For the loglinear interpolation , the combined
C04-1006 shown that both the linear and the loglinear interpolation of lexicon counts
D08-1091 and Gao ( 2007 ) . Fitting the loglinear model involves the following
C04-1006 polationresemblesmoreaunionofthetwolex - ica whereas the loglinear interpolation is more similar
C04-1032 and Ney , 2003 ) . Model 6 is a loglinear combination of the IBM-4 , IBM-1
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