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Results: 44
Number of items: 44
  • Open Access
    Rau, D., Dehghani, M., & Kamps, J. (2024). Revisiting Bag of Words Document Representations for Efficient Ranking with Transformers. ACM Transactions on Information Systems, 42(5), Article 114. https://doi.org/10.1145/3640460
  • Open Access
    Vardasbi, A. (2023). Re-examining assumptions in fair and unbiased learning to rank. [Thesis, fully internal, Universiteit van Amsterdam].
  • Vardasbi, A., de Rijke, M., & Dehghani, M. (2022). Intersection of Parallels as an Early Stopping Criterion. In CIKM '22: proceedings of the 31st ACM International Conference on Information & Knowledge Management : October 17-21, 2022, Atlanta, GA, USA (pp. 1965-1974). The Association for Computing Machinery. https://doi.org/10.1145/3511808.3557366
  • Open Access
    Azarbonyad, H., Dehghani, M., Marx, M., & Kamps, J. (2021). Learning to rank for multi-label text classification: Combining different sources of information. Natural Language Engineering, 27(1), 89-111. https://doi.org/10.1017/S1351324920000029
  • Open Access
    Dehghani, M. (2020). Learning with imperfect supervision for language understanding. [Thesis, fully internal, Universiteit van Amsterdam]. Institute for Logic, Language and Computation.
  • Open Access
    Dehghani, M., Azarbonyad, H., Kamps, J., & de Rijke, M. (2019). Learning to Transform, Combine, and Reason in Open-Domain Question Answering. In K. Beuls, B. Bogaerts, G. Bontempi, P. Geurts, N. Harley, B. Lebichot, T. Lenaerts, G. Louppe, & P. Van Eecke (Eds.), Proceedings of the 31st Benelux Conference on Artificial Intelligence (BNAIC 2019) and the 28th Belgian Dutch Conference on Machine Learning (Benelearn 2019): Brussels, Belgium, November 6-8, 2019 Article 16 (CEUR Workshop Proceedings; Vol. 2491). CEUR-WS. http://ceur-ws.org/Vol-2491/abstract16.pdf
  • Open Access
    Azarbonyad, H., Dehghani, M., Kenter, T., Marx, M., Kamps, J., & de Rijke, M. (2019). HiTR: Hierarchical Topic Model Re-estimation for Measuring Topical Diversity of Documents. IEEE Transactions on Knowledge and Data Engineering, 31(11), 2124-2137 . https://doi.org/10.1109/TKDE.2018.2874246
  • Open Access
    Dehghani, M., Azarbonyad, H., Kamps, J., & de Rijke, M. (2019). Learning to Transform, Combine, and Reason in Open-domain Question Answering. In WSDM'19: proceedings of the Twelfth ACM International Conference on Web Search and Data Mining : February 11-15, 2019 : Melbourne, Australia (pp. 681–689). Association for Computing Machinery. https://doi.org/10.1145/3289600.3291012
  • Open Access
    Dehghani, M., Mehrjou, A., Gouws, S., Kamps, J., & Schölkopf, B. (2019). Learning from Samples of Variable Quality. In Learning from Limited Labeled Data: ICLR 2019 Workshop OpenReview. https://openreview.net/forum?id=SkxwBgpmDE
  • Torkzadeh mahani, N., Dehghani, M., Mirian, M. S., Shakery, A., & Taheri, K. (2018). Expert finding by the Dempster‐Shafer theory for evidence combination. Expert Systems, 35(1), Article 12231. https://doi.org/10.1111/exsy.12231
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