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Results: 29
Number of items: 29
  • Open Access
    Tran, K., Bisazza, A., & Monz, C. (2018). The Importance of Being Recurrent for Modeling Hierarchical Structure. In E. Riloff, D. Chiang, J. Hockenmaier, & J. Tsujii (Eds.), Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing : EMNLP 2018: Brussels, Belgium, Oct. 31-Nov. 4 (pp. 4731–4736). The Association for Computational Linguistics. https://doi.org/10.18653/v1/D18-1503
  • Open Access
    Tran, K. (2018). Predicting and discovering linguistic structure with neural networks. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    Fadaee, M., Bisazza, A., & Monz, C. (2018). Examining the Tip of the Iceberg: A Data Set for Idiom Translation. In N. Calzolari, K. Choukri, C. Cieri, T. Declerck, S. Goggi, K. Hasida, H. Isahara, B. Maegaard, J. Mariani, H. Mazo, A. Moreno, J. Odijk, S. Piperidis, & T. Tokunaga (Eds.), LREC 2018 : Eleventh International Conference on Language Resources and Evaluation: May 7-12, 2018, Miyazaki, Japan (pp. 925-929). European Language Resources Association (ELRA). http://www.lrec-conf.org/proceedings/lrec2018/summaries/432.html
  • Open Access
    Fadaee, M., Bisazza, A., & Monz, C. (2017). Data Augmentation for Low-Resource Neural Machine Translation. In R. Barzilay, & M.-Y. Kan (Eds.), The 55th Annual Meeting of the Association for Computational Linguistics: proceedings of the Conference : July 30-August 4, 2017, Vancouver, Canada (Vol. 2, pp. 567-573). Association for Computational Linguistics. https://doi.org/10.18653/v1/P17-2090
  • Open Access
    van der Wees, M. E. (2017). What’s in a domain? Towards fine-grained adaptation for machine translation. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    van der Wees, M., Bisazza, A., & Monz, C. (2017). Dynamic Data Selection for Neural Machine Translation. In M. Palmer, R. Hwa, & S. Riedel (Eds.), The Conference on Empirical Methods in Natural Language Processing: proceedings of the conference : EMNLP 2017 : September 9-11, 2017, Copenhagen, Denmark (pp. 1400-1410). Association for Computational Linguistics. https://doi.org/10.18653/v1/D17-1147
  • Open Access
    Fadaee, M., Bisazza, A., & Monz, C. (2017). Learning Topic-Sensitive Word Representations. In R. Barzilay, & M.-Y. Kan (Eds.), The 55th Annual Meeting of the Association for Computational Linguistics: proceedings of the Conference : July 30-August 4, 2017, Vancouver, Canada (Vol. 2, pp. 441-447). Association for Computational Linguistics. https://doi.org/10.18653/v1/P17-2070
  • Open Access
    van der Wees, M., Bisazza, A., & Monz, C. (2016). Measuring the Effect of Conversational Aspects on Machine Translation Quality. In Y. Matsumoto, & R. Prasad (Eds.), Proceedings of COLING 2016: technical papers: the 26th International Conference on Computational Linguistics : Osaka, Japan, December 11-17 2016 (pp. 2571-2581). The COLING 2016 Organizing Committee. http://aclweb.org/anthology/C16-1242
  • Open Access
    Tran, K., Bisazza, A., & Monz, C. (2016). Recurrent Memory Networks for Language Modeling. In K. Knight, A. Nenkova, & O. Rambow (Eds.), NAACL HLT 2016 : The 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Proceedings of the Conference : June 12-17, 2016, San Diego, California, USA (pp. 321-331). The Association for Computational Linguistics. https://doi.org/10.18653/v1/N16-1036
  • Open Access
    Bisazza, A., & Federico, M. (2016). A Survey of Word Reordering in Statistical Machine Translation: Computational Models and Language Phenomena. Computational Linguistics, 42(2), 163-205. https://doi.org/10.1162/COLI_a_00245
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