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EMNLP
2007
15 years 8 months ago
Syntactic Re-Alignment Models for Machine Translation
We present a method for improving word alignment for statistical syntax-based machine translation that employs a syntactically informed alignment model closer to the translation m...
Jonathan May, Kevin Knight
LREC
2008
155views Education» more  LREC 2008»
15 years 8 months ago
Using Reordering in Statistical Machine Translation based on Alignment Block Classification
Statistical Machine Translation (SMT) is based on alignment models which learn from bilingual corpora the word correspondences between source and target language. These models are...
Marta R. Costa-Jussà, José A. R. Fon...
RIVF
2008
15 years 8 months ago
Simple but effective methods for combining kernels in computational biology
Complex biological data generated from various experiments are stored in diverse data types in multiple datasets. By appropriately representing each biological dataset as a kernel ...
Hiroaki Tanabe, Tu Bao Ho, Canh Hao Nguyen, Saori ...
NIPS
2000
15 years 8 months ago
A Neural Probabilistic Language Model
A goal of statistical language modeling is to learn the joint probability function of sequences of words in a language. This is intrinsically difficult because of the curse of dim...
Yoshua Bengio, Réjean Ducharme, Pascal Vinc...
GECCO
2008
Springer
137views Optimization» more  GECCO 2008»
15 years 7 months ago
Informative sampling for large unbalanced data sets
Selective sampling is a form of active learning which can reduce the cost of training by only drawing informative data points into the training set. This selected training set is ...
Zhenyu Lu, Anand I. Rughani, Bruce I. Tranmer, Jos...
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