N10-1139 using a standard single-source shortest-path algorithm . 4.2 Efficient method
H93-1033 breadth-first search implements a " shortest-path " heuristic -- we prefer the
D14-1049 to see the performance of the shortest-path method with respect to the syntactic
D11-1127 of target LM intersection and shortest-path algorithms that follow . Intersection
D11-1127 automata and give intersection , shortest-path and related algorithms that will
D15-1072 the alignment of two flows as a shortest-path search . We normalize the flows
D15-1286 algebraic structure necessary for shortest-path algorithms and can be derived
D14-1049 We also show the results for a shortest-path system trained and tested with
D14-1049 is to formulate SRL in terms of shortest-path inference , on the assumption
N09-1049 determinization , minimization and shortest-path , we find this search procedure
E97-1017 translations . We use Dijkstra 's shortest-path algorithm ( Dijkstra , 1959 )
C96-1046 major deficiency of the simple shortest-path length heuristic is that the
N12-1024 without constructing F n G to run a shortest-path algorithm on it . 2.2 Dual Decomposition
J98-4003 translations . The first is Dijkstra 's shortest-path graph algorithm ( Dijkstra 1959
D14-1049 will allow to employ efficient shortest-path inference , which is the main
N10-1139 approximation and is often used in shortest-path applications . Figure 1 ( a )
D14-1049 2002 ) , which directly employs shortest-path inference as part of the training
N10-1139 which is obtained by applying a shortest-path algorithm to − A ( H )
D14-1049 property allows for efficient shortest-path al gorithms that , given a predicate
D14-1049 parsing in terms of efficient shortest-path in - ference , under the assumption
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