C90-2071 |
considerations arising from the
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phrase and context . Figure 1
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C90-3012 |
on various types of syntactic
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constructions in Germanic languages
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C92-2072 |
thus , we would include multiple
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constructions , poten - ACT ,
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C92-2095 |
eliminate unnecessary center -
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; and ( 3 ) eliminating of scrambling
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C92-3137 |
re-Evaluation of the attitude in the
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attitude contexts . Thus , ill
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C96-1045 |
indirectly in terms of a homomorphic
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into Quasi Logical Form ( QLF
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D08-1086 |
investigated , and then a LVCSR system
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the presented analyzer is evaluated
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D10-1116 |
thus maintaining a reasonable
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capacity . 1 Introduction Steganography
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D12-1086 |
based on Euclidean co-occurrence
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combines the paradigmatic context
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D14-1012 |
effectively incorporating the word
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features within the framework
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D14-1012 |
prototype approach , for utilizing the
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features . The presented approaches
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D14-1012 |
approaches can better utilize the word
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features , among which the distributional
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D14-1012 |
outperforming the dense and continuous
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features by nearly 2 points of
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D14-1015 |
investigate how to improve bilingual
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which has been successfully used
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D14-1015 |
translation ( SMT ) . Despite bilingual
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's success , the contextual information
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D14-1015 |
memory-efficient model for learning bilingual
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, taking both the source phrase
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D14-1015 |
generated from our proposed bilingual
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model are used as features in
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D14-1030 |
some learned representation (
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) , and ( 3 ) compute output
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D14-1030 |
Sec - ondly , the neural network
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of word i can predict the MEG
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D14-1062 |
relevance for the in-domain task . By
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our latent domain phrase model
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