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CORR
2016
Springer

Bandit Structured Prediction for Learning from Partial Feedback in Statistical Machine Translation

3 years 3 months ago
Bandit Structured Prediction for Learning from Partial Feedback in Statistical Machine Translation
We present an approach to structured prediction from bandit feedback, called Bandit Structured Prediction, where only the value of a task loss function at a single predicted point, instead of a correct structure, is observed in learning. We present an application to discriminative reranking in Statistical Machine Translation (SMT) where the learning algorithm only has access to a 1 − BLEU loss evaluation of a predicted translation instead of obtaining a gold standard reference translation. In our experiment bandit feedback is obtained by evaluating BLEU on reference translations without revealing them to the algorithm. This can be thought of as a simulation of interactive machine translation where an SMT system is personalized by a user who provides single point feedback to predicted translations. Our experiments show that our approach improves translation quality and is comparable to approaches that employ more informative feedback in learning.
Artem Sokolov, Stefan Riezler, Tanguy Urvoy
Added 31 Mar 2016
Updated 31 Mar 2016
Type Journal
Year 2016
Where CORR
Authors Artem Sokolov, Stefan Riezler, Tanguy Urvoy
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