W12-3147 a different seed value for the optimisation algorithm . In this way we have a rough
W11-2158 a different seed value for the optimisation algorithm . In this way we have an rough
W10-1716 a different seed value for the optimisation algorithm . In this way we have an rough
W09-3938 The complete k-nn version policy optimisation algorithm is described in Algorithm 1 .
W12-6219 a hypothesis set CS . The line optimisation algorithm is then embedded within a general
J79-1058 language deciphering in terms of an optimisation algorithm . A definition of a language
S10-1053 result of the automatic parameter optimisation algorithm . Selecting different feature
W11-4413 matching algorithms are needed and optimisation algorithms would need to be examined . <title>
A00-2004 DotPlot Five versions of Reynar 's optimisation algorithm ( Reynar , 1998 ) were evaluated
P04-1014 parallel implementation of the L-BFGS optimisation algorithm is described , which runs on
P14-1116 evaluation in order to train an optimisation algorithm to perform summarisation according
W09-3938 The Monte-Carlo control policy optimisation algorithm is complemented with a k-nearest
D13-1176 data sets , hyper parameters and optimisation algorithms used for the training of the
D14-1063 benefits of the representation optimisation algorithm of section 4 . We use our Syntactic-dependency
P09-2077 makes it possible to extend an optimisation algorithm used in natural language generation
N13-1035 solved with standard numerical optimisation algorithms such as L-BFGS ( Byrd et al.
W11-2810 representation of the content and apply an optimisation algorithm for network analysis ( i.e. a
W12-6219 described a lattice-based line optimisation algorithm which can be incorporated into
P10-3002 the existing POMDP planning and optimisation algorithms , but rather complements them
P06-1088 al. , 1997 ) . We use the L-BFGS optimisation algorithm ( Nocedal and Wright , 1999 ;
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