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Dr. W. (Wilker) Ferreira Aziz

Faculteit der Natuurwetenschappen, Wiskunde en Informatica
ILLC

Bezoekadres
  • Science Park 105
Postadres
  • Postbus 94242
    1090 GE Amsterdam
Contactgegevens
  • Publicaties

    2020

    • Ataman, D., Ferreira Aziz, W., & Birch, A. (2020). A Latent Morphology Model for Open-Vocabulary Neural Machine Translation. In International Conference on Learning Representations https://openreview.net/pdf?id=BJxSI1SKDH
    • Correia, G. M., Niculae, V., Ferreira Aziz, W., & Martins, A. F. T. (2020). Efficient Marginalization of Discrete and Structured Latent Variables via Sparsity. In Efficient Marginalization of Discrete and Structured Latent Variables via Sparsity (pp. 11789-11802). Neural Information Processing Systems (NIPS) Foundation. https://papers.neurips.cc/paper/2020/hash/887caadc3642e304ede659b734f79b00-Abstract.html
    • De Cao, N., Schlichtkrull, M., Aziz, W., & Titov, I. (2020). How do Decisions Emerge across Layers in Neural Models? Interpretation with Differentiable Masking. In B. Webber, T. Cohn, Y. He, & Y. Liu (Eds.), 2020 Conference on Empirical Methods in Natural Language Processing: EMNLP 2020 : proceedings of the conference : November 16-20, 2020 (pp. 3243–3255). The Association for Computational Linguistics. https://doi.org/10.18653/v1/2020.emnlp-main.262 [details]
    • Eikema, B., & Aziz, W. (2020). Is MAP Decoding All You Need? The Inadequacy of the Mode in Neural Machine Translation. In D. Scott, N. Bel, & C. Zong (Eds.), The 28th International Conference on Computational Linguistics: COLING 2020 : Proceedings of the Conference : December 8-13, 2020, Barcelona, Spain (Online) (pp. 4506–4520). International Committee on Computational Linguistics. https://doi.org/10.18653/v1/2020.coling-main.398 [details]
    • Pelsmaeker, T., & Aziz, W. (2020). Effective Estimation of Deep Generative Language Models. In D. Jurafsky, J. Chai, N. Schluter, & J. Tetreault (Eds.), The 58th Annual Meeting of the Association for Computational Linguistics: ACL 2020 : Proceedings of the Conference : July 5-10, 2020 (pp. 7220-7236). The Association for Computational Linguistics. http://10.18653/v1/2020.acl-main.646 [details]

    2019

    • Bastings, J., Aziz, W., & Titov, I. (2019). Interpretable Neural Predictions with Differentiable Binary Variables. In A. Korhonen, D. Traum, & L. Màrquez (Eds.), The 57th Annual Meeting of the Association for Computational Linguistics: ACL 2019 : proceedings of the conference : July 28-August 2, 2019, Florence, Italy (pp. 2963-2977). Stroudsburg, PA: The Association for Computational Linguistics. https://doi.org/10.18653/v1/P19-1284 [details]
    • Calixto, I., Rios, M., & Aziz, W. (2019). Latent Variable Model for Multi-modal Translation. In A. Korhonen, D. Traum, & L. Màrquez (Eds.), The 57th Annual Meeting of the Association for Computational Linguistics: ACL 2019 : proceedings of the conference : July 28-August 2, 2019, Florence, Italy (pp. 6392–6405). Stroudsburg, PA: The Association for Computational Linguistics. https://doi.org/10.18653/v1/P19-1642 [details]
    • De Cao, N., Aziz, W., & Titov, I. (2019). Question answering by reasoning across documents with graph convolutional networks. In J. Burstein, C. Doran, & T. Solorio (Eds.), The 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: NAACL HLT 2019 : proceedings of the conference : June 2-June 7, 2019 (Vol. 1, pp. 2306-2317). Stroudsburg, PA: The Association for Computational Linguistics. https://doi.org/10.18653/v1/N19-1240 [details]
    • De Cao, N., Ferreira Aziz, W., & Titov, I. A. (2019). Block Neural Autoregressive Flow. In Proceedings of the the 35th Uncertainty in Artificial Intelligence Conference AUAI Press.
    • Eikema, B., & Aziz, W. (2019). Auto-Encoding Variational Neural Machine Translation. In I. Augenstein, S. Gella, S. Ruder, K. Kann, J. Welbl, A. Conneau, X. Ren, ... M. Rei (Eds.), The 4th Workshop on Representation Learning for NLP (RepL4NLP-2019): ACL 2019 : proceedings of the workshop : August 2, 2019, Florence, Italy (pp. 124–141). Stroudsburg, PA: The Association for Computational Linguistics. https://doi.org/10.18653/v1/W19-4315 [details]

    2018

    • Rios, M., Aziz, W., & Sima'an, K. (2018). Deep Generative Model for Joint Alignment and Word Representation. In M. Walker, H. Ji, & A. Stent (Eds.), NAACL-HLT 2018 : The 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: proceedings of the conference : June 1-June 6, 2018, New Orleans, Louisiana (Vol. 1, pp. 1011-1023). Stroudsburg, PA: The Association for Computational Linguistics. https://doi.org/10.18653/v1/N18-1092 [details]
    • Schulz, P., Aziz, W., & Cohn, T. (2018). A Stochastic Decoder for Neural Machine Translation. In I. Gurevych, & Y. Miyao (Eds.), ACL 2018 : The 56th Annual Meeting of the Association for Computational Linguistics: proceedings of the conference : July 15-20, 2018, Melbourne, Australia (Vol. 1, pp. 1243-1252). Stroudsburg, PA: The Association for Computational Linguistics. https://doi.org/10.18653/v1/P18-1115 [details]

    2017

    • Bastings, J., Titov, I., Aziz, W., Marcheggiani, D., & Sima'an, K. (2017). Graph Convolutional Encoders for Syntax-aware Neural Machine Translation. In M. Palmer, R. Hwa, & S. Riedel (Eds.), Conference on Empirical Methods in Natural Language Processing: emnlp20017 : Copenhagen, Denmark, September 7-11, 2017 : conference proceedings: September 9-11, 2017, Copenhagen, Denmark (pp. 1957-1967). Stroudsburg, PA: The Association for Computational Linguistics. https://doi.org/10.18653/v1/D17-1209 [details]

    2016

    • Daiber, J., Stanojević, M., Aziz, W., & Sima'an, K. (2016). Examining the Relationship between Preordering and Word Order Freedom in Machine Translation. In Proceedings of the First Conference on Machine Translation: Berlin, Germany, August 11-12, 2016 (Vol. 1, pp. 118-130). Stroudsburg, PA: Association for Computational Linguistics. https://doi.org/10.18653/v1/W16-2213 [details]
    • Schulz, P., & Aziz, W. (2016). Fast Collocation-Based Bayesian HMM Word Alignment. 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. 3146-3155). The COLING 2016 Organizing Committee. [details]
    • Schulz, P., Aziz, W., & Sima'an, K. (2016). Word Alignment without NULL words. In K. Erk, & N. A. Smith (Eds.), The 54th Annual Meeting of the Association for Computational Linguistics : ACL 2016: proceedings of the conference : August 7-12, 2016, Berlin Germany (Vol. 2, pp. 169-174). Stroudsburg, PA: Association for Computational Linguistics. https://doi.org/10.18653/v1/P16-2028 [details]

    2015

    2014

    • Aziz, W., Dymetman, M., & Specia, L. (2014). Exact Decoding for Phrase-Based Statistical Machine Translation. In A. Moschitti, B. Pang, & W. Daelemans (Eds.), EMNLP 2014: the 2014 Conference on Empirical Methods In Natural Language Processing: proceedings of the conference: October 25-29, 2014, Doha, Qatar (pp. 1237-1249). Stroudsburg, PA: Association for Computational Linguistics. [details]

    2020

    • De Cao, N., & Ferreira Aziz, W. (2020). The Power Spherical distribution. Paper presented at ICML 2020 workshop INNF+: Invertible Neural Networks, Normalizing Flows, and Explicit Likelihood Models. https://arxiv.org/abs/2006.04437

    Prijs

    • Eikema, B. & Aziz, W. (2020). COLING Best Paper Award.

    2020

    • Bastings, J. (2020). A tale of two sequences: Interpretable and linguistically-informed deep learning for natural language processing. Institute for Logic, Language and Computation. [details]
    • Del Tredici, M. (2020). Linguistic variation in online communities: A computational perspective. Institute for Logic, Language and Computation. [details]
    • Schulz, P. (2020). Latent variable models for machine translation and how to learn them. Institute for Logic, Language and Computation. [details]

    2018

    • Daiber, J. (2018). Typologically robust statistical machine translation: Understanding and exploiting differences and similarities between languages in machine translation. [details]

    2017

    • Stanojević , M. (2017). Permutation forests for modeling word order in machine translation. [details]
    This list of publications is extracted from the UvA-Current Research Information System. Questions? Ask the library or the Pure staff of your faculty / institute. Log in to Pure to edit your publications. Log in to Personal Page Publication Selection tool to manage the visibility of your publications on this list.
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