N10-1129 path , thus complicating future cost estimation . We would need to evaluate all
J15-2001 is caused by inaccurate future cost estimation . Using phrases helps phrase-based
W09-1903 investigation of the annotation cost estimation task for active learning in a
J15-2001 in their experiments . Future Cost Estimation : A third problem is caused by
W09-1903 characteristics for annotation cost estimation . 3.4.3 CRCoef Vs. RMS We presented
P10-1064 the upper-bound of the related cost estimation . Finally , we analyze the characteristics
D11-1083 using heuristics based on future cost estimation . In general the estimation of
P09-2073 process to automate the procedure of cost estimation . 3 Particle Swarm Optimization
N06-2051 system with reordering and future cost estimation . We trained translation parameters
W01-1408 overhead of performing this rest cost estimation for every coverage set in search
N13-3003 , and established localisation cost estimation models based on TM technologies
W05-0834 rest cost estimation . As rest cost estimation , the negated logarithm of the
W09-1903 linear regression for annotation cost estimation for Part-Of-Speech ( POS ) tagging
S15-1030 dimensional vectors ) for the costs estimation . Table 4 presents the results
W05-0836 pruning as well as the future cost estimation used in the Pharaoh and CMU decoders
W09-1903 as features in the annotation cost estimation . A model trained on data from
N10-1129 independent components . 3.1 Future Cost Estimation Despite its lack of sophistication
N10-1129 Figure 5 ) . As expected , future cost estimation alone does not increase performance
W05-0834 translation candidate . + The rest cost estimation is not ef cient . It has an exponential
D12-1109 parsing strategy and dynamic future cost estimation for each partial trans - lation
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