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Results: 35
Number of items: 35
  • de Leon-Martinez, S., Kang, J., Móro, R., de Rijke, M., Kveton, B., Oosterhuis, H., & Bielikova, M. (2025, April 29). RecGaze Dataset - Public Version [Data set]. Zenodo. https://doi.org/10.5281/zenodo.15270518
  • Open Access
    Gupta, S. (2025). Safe, efficient and robust reinforcement learning for ranking and diffusion models. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    Gupta, S., Hager, P., Huang, J., Vardasbi, A., & Oosterhuis, H. (2024). Unbiased Learning to Rank: On Recent Advances and Practical Applications. In WSDM '24: Proceedings of the 17th ACM International Conference on Web Search and Data Mining : March 4-8, 2024, Merida, Mexico (pp. 1118–1121). Association for Computing Machinery. https://doi.org/10.1145/3616855.3636451
  • Open Access
    Gupta, S., Oosterhuis, H., & de Rijke, M. (2024). Practical and Robust Safety Guarantees for Advanced Counterfactual Learning to Rank. In CIKM '24: Proceedings of the 33rd ACM International Conference on Information and Knowledge Management : October, 21-25. 2024, Boise, ID, USA (pp. 737-747). Association for Computing Machinery. https://doi.org/10.1145/3627673.3679531
  • Open Access
    Huang, J., Oosterhuis, H., Mansoury, M., van Hoof, H., & de Rijke, M. (2024). Going Beyond Popularity and Positivity Bias: Correcting for Multifactorial Bias in Recommender Systems. In SIGIR '24: Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval : July 14-18, 2024, Washington, DC, USA (pp. 416-426). Association for Computing Machinery. https://doi.org/10.1145/3626772.3657749
  • Open Access
    Huang, J. (2024). Learning recommender systems from biased user interactions. [Thesis, fully internal, Universiteit van Amsterdam].
  • Gupta, S., Hager, P., & Oosterhuis, H. (2023). Recent Advancements in Unbiased Learning to Rank. In D. Ganguly, S. Majumdar, B. Mitra, P. Gupta, S. Gangopadhyay, & P. Majemder (Eds.), FIRE 2023: Proceedings of the 15th annual meeting of the Forum for Information Retrieval Evaluation : Goa University, Panjim, India, December 15-18, 2023 (pp. 145-148). (ACM International Conference Proceedings Series). The Association for Computing Machinery. https://doi.org/10.1145/3632754.3632942
  • Open Access
    Gupta, S., Oosterhuis, H., & de Rijke, M. (2023). A Deep Generative Recommendation Method for Unbiased Learning from Implicit Feedback. In ICTIR '23: Proceedings of the 2023 ACM SIGIR International Conference on Theory of Information Retrieval : July 23, 2023, Taipei, Taiwan (pp. 87–93). Association for Computing Machinery. https://doi.org/10.1145/3578337.3605114
  • Open Access
    Gupta, S., Hager, P., Huang, J., Vardasbi, A., & Oosterhuis, H. (2023). Recent Advances in the Foundations and Applications of Unbiased Learning to Rank. In SIGIR '23: Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval : July 23-27, 2023, Taipei, Taiwan (pp. 3440–3443). Association for Computing Machinery. https://doi.org/10.1145/3539618.3594247
  • Open Access
    Gupta, S., Oosterhuis, H., & de Rijke, M. (2023). Safe Deployment for Counterfactual Learning to Rank with Exposure-Based Risk Minimization. In SIGIR '23: Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval : July 23-27, 2023, Taipei, Taiwan (pp. 249–258). Association for Computing Machinery. https://doi.org/10.1145/3539618.3591760
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