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Results: 163
Number of items: 163
  • 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
  • Ghader, H., & Monz, C. (2017). What does Attention in Neural Machine Translation Pay Attention to? In G. Kondrak, & T. Watanabe (Eds.), The Eight International Joint Conference on Natural Language Processing: proceedings of the Conference : November 27-December 1, 2017, Taipei, Taiwan (Vol. 1, pp. 30-39). Asian Federation of Natural Language Processing. http://www.aclweb.org/anthology/I17-1004
  • 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
    Garmash, E. (2017). Exploring the correspondence between languages for machine translation. [Thesis, fully internal, Universiteit van Amsterdam].
  • 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
    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].
  • Bellegarda, J. R., & Monz, C. (2016). State of the Art in Statistical Methods for Language and Speech Processing. Computer Speech and Language, 35, 163-184. https://doi.org/10.1016/j.csl.2015.07.001
  • Open Access
    Garmash, E., & Monz, C. (2016). Ensemble Learning for Multi-Source Neural Machine Translation. 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. 1409-1418). The COLING 2016 Organizing Committee. https://www.aclweb.org/anthology/C16-1133
  • Open Access
    Martzoukos, S. (2016). Combinatorial and compositional aspects of bilingual aligned corpora. [Thesis, fully internal, Universiteit van Amsterdam].
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