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» Learning Finite-State Models for Machine Translation
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COLING
2010
14 years 4 months ago
Log-linear weight optimisation via Bayesian Adaptation in Statistical Machine Translation
We present an adaptation technique for statistical machine translation, which applies the well-known Bayesian learning paradigm for adapting the model parameters. Since state-of-t...
Germán Sanchis-Trilles, Francisco Casacuber...
ACL
2006
14 years 11 months ago
Modelling Lexical Redundancy for Machine Translation
Certain distinctions made in the lexicon of one language may be redundant when translating into another language. We quantify redundancy among source types by the similarity of th...
David Talbot, Miles Osborne
EMNLP
2011
13 years 9 months ago
Watermarking the Outputs of Structured Prediction with an application in Statistical Machine Translation
We propose a general method to watermark and probabilistically identify the structured outputs of machine learning algorithms. Our method is robust to local editing operations and...
Ashish Venugopal, Jakob Uszkoreit, David Talbot, F...
EMNLP
2009
14 years 7 months ago
Synchronous Tree Adjoining Machine Translation
Tree Adjoining Grammars have well-known advantages, but are typically considered too difficult for practical systems. We demonstrate that, when done right, adjoining improves tran...
Steve DeNeefe, Kevin Knight
ICML
2009
IEEE
15 years 10 months ago
Predictive representations for policy gradient in POMDPs
We consider the problem of estimating the policy gradient in Partially Observable Markov Decision Processes (POMDPs) with a special class of policies that are based on Predictive ...
Abdeslam Boularias, Brahim Chaib-draa