language grammar 0.00286314
grammar models 0.00233434
dependency grammar 0.002221408
grammar learning 0.002185816
language grammars 0.001976637
grammar parameters 0.001974882
grammar rule 0.001969957
unsupervised grammar 0.001953819
random grammar 0.001946916
grammar rules 0.0019372859999999999
form grammar 0.0019208089999999999
likelihood grammar 0.001916755
language sentences 0.0019025119999999999
initial grammar 0.0018964539999999999
natural language 0.0018661630000000001
dependency model 0.0018648480000000001
grammar symbols 0.001843173
grammar induction 0.0018314899999999999
target grammar 0.001821992
dency grammar 0.001817
supervised grammar 0.0018118119999999999
sparse grammar 0.00180438
art grammar 0.001794124
language sentence 0.0017874269999999999
pervised grammar 0.001786301
vanced grammar 0.001780861
english language 0.001708567
language gram 0.001692491
good model 0.001655533
ral language 0.001576519
grammar 0.00155307
language evolution 0.001549735
language parsers 0.001546466
ural language 0.001538486
dmv model 0.001528744
model posteriors 0.001435082
same distribution 0.001359119
language 0.00131007
training data 0.001267538
probability distribution 0.001223893
model 0.00119651
posterior distribution 0.001131406
dependency accuracy 0.001130592
different values 0.0011271599999999999
training sentences 0.001087274
unsupervised dependency 0.001069087
training corpus 0.0010582539999999998
probabilistic grammars 0.0010562879999999998
different priors 0.0010511329999999999
pendency models 0.001050826
dependency gram 0.001050759
extended models 0.001047357
iterative algorithm 0.001045432
unlabeled data 0.001037474
data samples 0.001036319
bias learning 0.001034447
unsupervised learning 0.001033495
objective function 0.001029331
labeled data 0.001026902
table learning 0.001018451
other types 0.001015032
ing sentences 0.001013865
uniform distribution 0.001010719
advanced models 0.001010239
other approaches 0.001008699
image data 0.00100216
accuracy value 9.89897E-4
different settings 9.857759999999998E-4
unambiguous grammars 9.82129E-4
additional parameter 9.76598E-4
training sentence 9.721889999999999E-4
auxiliary distribution 9.606199999999999E-4
other hand 9.574539999999999E-4
such approaches 9.57051E-4
iary distribution 9.54973E-4
possible parses 9.43777E-4
same point 9.40006E-4
machine learning 9.32035E-4
learning algorithms 9.30001E-4
unambiguity regularization 9.299079999999999E-4
example sentence 9.27092E-4
parsing accuracy 9.2202E-4
dependency accuracies 9.12276E-4
log probabilities 9.03109E-4
posterior regularization 9.013129999999999E-4
large value 8.992199999999999E-4
dependency accu 8.968649999999999E-4
short sentences 8.88947E-4
parameter sparsity 8.84699E-4
prior distributions 8.811649999999999E-4
timization problem 8.769100000000001E-4
previous results 8.73328E-4
additional regularization 8.72601E-4
testing sentences 8.71708E-4
empirical results 8.69685E-4
variational inference 8.66281E-4
inference variational 8.66281E-4
probability distributions 8.656849999999999E-4
form probability 8.652810000000001E-4
rule probabilities 8.61314E-4
