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Results: 12
Number of items: 12
  • Jagerman, R., Markov, I., & de Rijke, M. (2020). Safe Exploration for Optimizing Contextual Bandits. ACM Transactions on Information Systems, 38(3), Article 24. https://doi.org/10.1145/3385670
  • Open Access
    Jagerman, R., & de Rijke, M. (2020). Accelerated Convergence for Counterfactual Learning to Rank. In SIGIR '20: proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval : July 25-30, 2020, virtual event, China (pp. 469–478). Association for Computing Machinery. https://doi.org/10.1145/3397271.3401069
  • Open Access
    Jagerman, R., Markov, I., & de Rijke, M. (2020). Safe Exploration for Optimizing Contextual Bandits. (pp. 23). ArXiv. https://doi.org/10.48550/arXiv.2002.00467
  • Open Access
    Jagerman, R. M. (2020). Efficient, safe and adaptive learning from user interactions. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    Oosterhuis, H., Jagerman, R., & de Rijke, M. (2020). Unbiased Learning to Rank: Counterfactual and Online Approaches. In The Web Conference 2020: companion of the World Wide Web Conference WWW 2020 : Taipei 2020 : April 20-24, 2020, Taipei, Taiwan (pp. 299-300). International World Wide Web Conference Committee. https://doi.org/10.1145/3366424.3383107
  • 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
  • Jagerman, R., Markov, I., & de Rijke, M. (2019). When people change their mind: Off-policy evaluation in non-stationary recommendation environments. In WSDM'19: proceedings of the Twelfth ACM International Conference on Web Search and Data Mining : February 11-15, 2019 : Melbourne, Australia (pp. 447-455). Association for Computing Machinery. https://doi.org/10.1145/3289600.3290958
  • Jagerman, R., Balog, K., & de Rijke, M. (2018). OpenSearch: Lessons Learned from an Online Evaluation Campaign. Journal of Data and Information Quality, 10(3), Article 13. https://doi.org/10.1145/3239575
  • Jagerman, R., Eickhoff, C., & de Rijke, M. (2017). Computing Web-scale Topic Models using an Asynchronous Parameter Server. In SIGIR'17 : proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval: August 7-11, 2017, Shinjuku, Tokyo, Japan (pp. 1337-1340). Association for Computing Machinery. https://doi.org/10.1145/3077136.3084135
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