| N10-1092 | Translation for which an efficient | Dynamic Programming parsing | algorithm exists . In this work |
| N10-1092 | correlate them . An efficient | Dynamic Programming parsing | algorithm for SITGs was presented |
| P04-1005 | model . The standard n5 bottom-up | dynamic programming parsing | algorithm can be used with this |
| W05-1503 | exactly the same way as usual in | dynamic programming parsing | . 3.1 Switch Graphs Switch graphs |
| P02-1036 | atomic entities manipulated by a | dynamic programming parsing | algorithm . A grammar defines |
| P04-1005 | model , and their polynomialtime | dynamic programming parsing | algorithms can be used to search |
| P09-1039 | intimately associated with Eisner 's | dynamic programming parsing | algorithm and with the Markovian |
| P11-1071 | model , and their polynomialtime | dynamic programming parsing | algorithms can be used to search |
| D11-1114 | literature . We then develop a | dynamic programming parsing | algorithm for our model , and |
| D11-1137 | is inspired by the third-order | dynamic programming parsing | algorithm ( Koo and Collins , |
| P05-1022 | straight-forward . The problem is space . | Dynamic programming parsing | algorithms for PCFGs require |
| P05-1022 | programming states , so direct | dynamic programming parsing | with the fine-grained grammar |
| P05-1022 | It is certainly possible to do | dynamic programming parsing | directly with the fine-grained |
