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Results: 9
Number of items: 9
  • Open Access
    Li, C. (2021). Optimizing ranking systems online as bandits. [Thesis, fully internal, Universiteit van Amsterdam].
  • Li, C., Markov, I., de Rijke, M., & Zoghi, M. (2020). MergeDTS: A Method for Effective Large-scale Online Ranker Evaluation. ACM Transactions on Information Systems, 38(4), Article 40. https://doi.org/10.1145/3411753
  • Open Access
    Li, C., Kveton, B., Lattimore, T., Markov, I., de Rijke, M., Szepesvári, C., & Zoghi, M. (2019). BubbleRank: Safe Online Learning to Re-Rank via Implicit Click Feedback. In A. Globerson, & R. Silva (Eds.), Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence: UAI 2019, Tel Aviv, Israel, July 22-25, 2019 Article 47 AUAI Press. http://auai.org/uai2019/proceedings/papers/47.pdf
  • Zoghi, M., Whiteson, S., & de Rijke, M. (2015). MergeRUCB: A method for large-scale online ranker evaluation. In WSDM'15: proceedings of the Eighth ACM International Conference on Web Search and Data Mining: Jan. 31-Feb. 6, 2015, Shanghai, China (pp. 17-26). Association for Computing Machinery. https://doi.org/10.1145/2684822.2685290
  • Zoghi, M., Whiteson, S., de Rijke, M., & Munos, R. (2014). Relative confidence sampling for efficient on-line ranker evaluation. In WSDM '14: proceedings of the 7th ACM International Conference on Web Search and Data Mining: February 24-28, 2014, New York, New York, USA (pp. 73-82). ACM. https://doi.org/10.1145/2556195.2556256
  • Open Access
    Zoghi, M., Whiteson, S., Munos, R., & de Rijke, M. (2014). Relative Upper Confidence Bound for the K-Armed Dueling Bandit Problem. JMLR Workshop and Conference Proceedings, 32, 10-18. http://jmlr.org/proceedings/papers/v32/zoghi14.html
  • Open Access
    van Eijk, N., Roessler, B., Zuiderveen Borgesius, F., Oostveen, M., et al., U., van Son, R., Verkade, F., Vliek, M., Alberdingk Thijm, C., Apt, K., Böhler, B., den Boon, A., Breemen, K., Breemen, V., de Goede, M., van Gompel, S., Guibault, L., Helberger, N., Hins, A. W., ... Taylor, L. (2014). Academics Against Mass Surveillance. Web publication or website, Academics Against Mass Surveillance. http://www.academicsagainstsurveillance.org/
  • Open Access
    Wang, Z., Zoghi, M., Hutter, F., Matheson, D., & de Freitas, N. (2013). Bayesian Optimization in High Dimensions via Random Embeddings. In F. Rossi (Ed.), IJCAI-13: proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence: Beijing, China, 3-9 August 2013. - Vol. 3 (pp. 1778-1784). AAAI Press/International Joint Conferences on Artificial Intelligence. http://www.aaai.org/Press/Proceedings/ijcai13.php
  • Open Access
    de Freitas, N., Smola, A. J., & Zoghi, M. (2012). Exponential Regret Bounds for Gaussian Process Bandits with Deterministic Observations. In J. Langford, & J. Pineau (Eds.), Proceedings of Twenty-Ninth International Conference Machine Learning. - Vol. 2 (pp. 1743-1750). International Machine Learning Society. http://www.icml.cc/2012/papers/853.pdf
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