W03-2002 different viewpoints , using the map algorithm described in section 2 . Before
H91-1053 adaptation data using the segmental MAP algorithm . The SI models are used to initialize
H93-1019 are obtained with the segmental MAP algorithm \ -LSB- 16 , 9 , 10 \ -RSB- using
W15-0807 mapping . The input of our mention - mapping algorithm is the pairwise scores between
H91-1053 state . The following segmental MAP algorithm originally proposed in \ -LSB-
H91-1053 -LSB- 131 we used the segmental MAP algorithm to evaluate the HMM parameters
H93-1019 initial estimate for the segmental MAP algorithm . This approach provides a way
P93-1003 possible correspondences . THE MAPPING ALGORITHM Some terminology is necessary
W94-0102 model . We are developing a set of mapping algorithms to map between the main tagsets
W94-0102 algorithm to be induced . 3 . Apply mapping algorithm to the parsed SEC ; incrementally
W02-0210 utilizing the Self-Organizing Map algorithm ( Kohonen , 1995 ) . The document
H94-1067 variations are shown in Table 4 . when mapping algorithm is used in different ways . The
H91-1053 approximately satisfied . Segmental MAP algorithm The above procedure to evaluate
J06-3008 algorithms . These two classes of mapping algorithms and the ranking of semantic roles
H91-1053 adaptation data using a segmental MAP algorithm which uses the Viterbi algorithm
W94-0102 on how much time is available , mapping algorithms for more detailed grammar schemes
D14-1031 most of the simulations the local MAP algorithm performs as well as the two other
H92-1036 If we use the forward-backward MAP algorithm we obtain a corrective training
P14-1056 equation ( 1 ) , for which we have a MAP algorithm , but where we have imposed some
W94-0102 mappings will be imperfect . As mapping algorithms are developed and tested , and
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