P14-1138 |
penalty function that ensures word
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embedding
|
consistency across two directional
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E89-1033 |
has been implemented , and an
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embedding
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of this in an interactive parsing
|
D15-1038 |
completion impute missing facts by
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embedding
|
knowledge graphs in vector spaces
|
P06-2071 |
from the image and text of the
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embedding
|
web page . We evaluate our method
|
P15-2002 |
show that , although an isometric
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embedding
|
is untractable , it is possible
|
S14-2011 |
provides dense , low-dimensional
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embedding
|
for each fragment which allows
|
C80-1074 |
Fl ) , nominalization ( FII ) ,
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embedding
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( fill ) , connecting ( FIV )
|
P10-1121 |
predicting reading times , and that
|
embedding
|
difference makes a significant
|
J00-3002 |
The unacceptability of centre
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embedding
|
is illustrated by the fact that
|
W10-2802 |
ularities . This latter is employed by
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embedding
|
prior FrameNet-derived knowledge
|
D14-1012 |
prototype approach , for utilizing the
|
embedding
|
features . The presented approaches
|
H90-1008 |
the second only does so if no
|
embedding
|
link exists at the current focus
|
C86-1088 |
first-order model structure . A proper
|
embedding
|
is a function from 1J / ~ to
|
D15-1183 |
, we propose a generative word
|
embedding
|
model , which is easy to interpret
|
N12-1088 |
input and output spaces . This
|
embedding
|
is learned in such a way that
|
J14-2006 |
secret bitstring , the secret
|
embedding
|
fails . Therefore , it is important
|
D15-1196 |
outperforms the state-of-the-art word
|
embedding
|
methods in both representation
|
H91-1106 |
the sentence generator ; and the
|
embedding
|
of all these parts into the joint
|
T87-1012 |
they all assiduously avoid center
|
embedding
|
in favor of strongly left - or
|
P13-1078 |
translation models with/without
|
embedding
|
features on Chinese-to-English
|