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The RWTH Aachen Machine Translation System for WMT 2013.

, , , , , , , and . WMT@ACL, page 193-199. The Association for Computer Linguistics, (2013)

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Empirical Investigation of Optimization Algorithms in Neural Machine Translation., , , , and . Prague Bull. Math. Linguistics, (2017)Alignment-Based Neural Machine Translation., , , , , and . WMT, page 54-65. The Association for Computer Linguistics, (2016)The RWTH Aachen University English-German and German-English Machine Translation System for WMT 2017., , , , , , , and . WMT, page 358-365. Association for Computational Linguistics, (2017)The RWTH Aachen Machine Translation System for IWSLT 2016., , , , and . IWSLT, International Workshop on Spoken Language Translation, (2016)(Hidden) Conditional Random Fields Using Intermediate Classes for Statistical Machine Translation., , , , and . MTSummit, (2013)A Comparison between Count and Neural Network Models Based on Joint Translation and Reordering Sequences., , , , and . EMNLP, page 1401-1411. The Association for Computational Linguistics, (2015)Advancements in Reordering Models for Statistical Machine Translation., , and . ACL (1), page 322-332. The Association for Computer Linguistics, (2013)Soft String-to-Dependency Hierarchical Machine Translation.. Informatiktage, volume S-11 of LNI, page 59-62. GI, (2012)The RWTH Aachen machine translation systems for IWSLT 2013., , , , , , and . IWSLT (Evaluation Campaign), (2013)An exploration of alignment concepts to bridge the gap between phrase-based and neural machine translation.. RWTH Aachen University, Germany, (2020)