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Results: 35
Number of items: 35
  • Open Access
    Oosterhuis, H. R. (2020). Learning from user interactions with rankings: A unification of the field. [Thesis, fully internal, Universiteit van Amsterdam].
  • Lucchesee, C., Nardini, F. M., Pasumarthi, R. K., Bruch, S., Bendersky, M., Wang, X., Oosterhuis, H., Jagerman, R., & de Rijke, M. (2019). Learning to Rank in Theory and Practice: From Gradient Boosting to Neural Networks and Unbiased Learning. In SIGIR '19: proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval : July 21-25, 2019, Paris, France (pp. 1419-1420). The Association for Computing Machinery. https://doi.org/10.1145/3331184.3334824
  • Jagerman, R., Oosterhuis, H., & de Rijke, M. (2019). To Model or to Intervene: A Comparison of Counterfactual and Online Learning to Rank from User Interactions. In SIGIR '19: proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval : July 21-25, 2019, Paris, France (pp. 15-24). The Association for Computing Machinery. https://doi.org/10.1145/3331184.3331269
  • Open Access
    Oosterhuis, H., & de Rijke, M. (2019). Optimizing Ranking Models in an Online Setting. In L. Azzopardi, B. Stein, N. Fuhr, P. Mayr, C. Hauff, & D. Hiemstra (Eds.), Advances in Information Retrieval: 41st European Conference on IR Research, ECIR 2019, Cologne, Germany, April 14-18, 2019 : proceedings (Vol. 1, pp. 382-396). (Lecture Notes in Computer Science; Vol. 11437). Springer. https://doi.org/10.1007/978-3-030-15712-8_25
  • Open Access
    Lucic, A., Oosterhuis, H., Haned, H., & de Rijke, M. (2019). Actionable Interpretability through Optimizable Counterfactual Explanations for Tree Ensembles. (v1 ed.) ArXiv.
  • Oosterhuis, H., & de Rijke, M. (2018). Ranking for Relevance and Display Preferences in Complex Presentation Layouts. In SIGIR #41 proceedings: Ann Arbor, Michigan, USA, 08-12, July 2018 (pp. 845-854). Association for Computing Machinery. https://doi.org/10.1145/3209978.3209992
  • Oosterhuis, H., & de Rijke, M. (2018). Differentiable Unbiased Online Learning to Rank. In CIKM'18: proceedings of the 2018 ACM International Conference on Information and Knowledge Management : October 22-26, 2018, Torino, Italy (pp. 1293-1302). The Association for Computing Machinery. https://doi.org/10.1145/3269206.3271686
  • Oosterhuis, H., Culpepper, J. S., & de Rijke, M. (2018). The Potential of Learned Index Structures for Index Compression. In B. Koopman, A. Trotman, & P. Thomas (Eds.), ADCS 2018: proceedings of the 23rd Australasian Document Computing Symposium : Dunedin, New Zealand, December 11-12, 2018 Article 7 ACM. https://doi.org/10.1145/3291992.3291993
  • Oosterhuis, H., & de Rijke, M. (2017). Sensitive and Scalable Online Evaluation with Theoretical Guarantees. In CIKM'17 : proceedings of the 2017 ACM on Conference on Information and Knowledge Management: November 6-10, 2017, Singapore, Singapore (pp. 77-86). Association for Computing Machinery. https://doi.org/10.1145/3132847.3132895
  • Oosterhuis, H., & de Rijke, M. (2017). Balancing Speed and Quality in Online Learning to Rank for Information Retrieval. In CIKM'17 : proceedings of the 2017 ACM on Conference on Information and Knowledge Management: November 6-10, 2017, Singapore, Singapore (pp. 277-286). Association for Computing Machinery. https://doi.org/10.1145/3132847.3132896
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