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Results: 1,025
Number of items: 1,025
  • Open Access
    de Rijke, M. (2019). Reinforcement learning to rank. 5. Abstract from 12th ACM International Conference on Web Search and Data Mining, WSDM 2019, Melbourne, Australia. https://doi.org/10.1145/3289600.3291605
  • Open Access
    Xie, X., Mao, J., Liu, Y., de Rijke, M., Shao, Y., Ye, Z., Zhang, M., & Ma, S. (2019). Grid-based Evaluation Metrics for Web Image Search. In The Web Conference 2019: proceedings of the World Wide Web Conference WWW 2019 : May 13-17, 2019, San Francisco, CA, USA (pp. 2103–2114). Association for Computing Machinery. https://doi.org/10.1145/3308558.3313514
  • Open Access
    Jiang, S., Ren, P., Monz, C., & de Rijke, M. (2019). Improving Neural Response Diversity with Frequency-Aware Cross-Entropy Loss. In The Web Conference 2019: proceedings of the World Wide Web Conference WWW 2019 : May 13-17, 2019, San Francisco, CA, USA (pp. 2879-2885). Association for Computing Machinery. https://doi.org/10.1145/3308558.3313415
  • Open Access
    van den Akker, B., Markov, I., & de Rijke, M. (2019). ViTOR: Learning to rank webpages based on visual features. In The Web Conference 2019: proceedings of the World Wide Web Conference WWW 2019 : May 13-17, 2019, San Francisco, CA, USA (pp. 3279-3285). Association for Computing Machinery. https://doi.org/10.1145/3308558.3313419
  • 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
  • Ren, P., Chen, Z., Ren, Z., Wei, F., Nie, L., Ma, J., & de Rijke, M. (2018). Sentence relations for extractive summarization with deep neural networks. ACM Transactions on Information Systems, 36(4), Article 39. https://doi.org/10.1145/3200864
  • Voskarides, N., Meij, E., Reinanda, R., Khaitan, A., Osborne, M., Stefanoni, G., Kambadur, P., & de Rijke, M. (2018). Weakly-supervised contextualization of knowledge graph facts. In SIGIR #41 proceedings : Ann Arbor, Michigan, USA, 08-12, July 2018 (pp. 765-774). Association for Computing Machinery. https://doi.org/10.1145/3209978.3210031
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