Poncelas, Alberto, Maillette de Buy Wenniger, Gideon, Way, Andy Feature Decay Algorithms for Neural Machine Translation Poncelas, Alberto; Maillette de Buy Wenniger, Gideon; Way, Andy. “Feature Decay Algorithms for Neural Machine Translation”. In: Pérez-Ortiz, Juan Antonio, et al. (Eds.). Proceedings of the 21st Annual Conference of the European Association for Machine Translation: 28-30 May 2018, Universitat d'Alacant, Alacant, Spain, pp. 239-248 URI: http://hdl.handle.net/10045/76084 DOI: ISSN: ISBN: 978-84-09-01901-4 Abstract: Neural Machine Translation (NMT) systems require a lot of data to be competitive. For this reason, data selection techniques are used only for fine-tuning systems that have been trained with larger amounts of data. In this work we aim to use Feature Decay Algorithms (FDA) data selection techniques not only to fine-tune a system but also to build a complete system with less data. Our findings reveal that it is possible to find a subset of sentence pairs, that outperforms by 1.11 BLEU points the full training corpus, when used for training a German-English NMT system. Keywords:Machine Translation European Association for Machine Translation info:eu-repo/semantics/conferenceObject