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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
  • Li, C., Feng, H., & de Rijke, M. (2020). Cascading Hybrid Bandits: Online Learning to Rank for Relevance and Diversity. In RECSYS 2020: 14th ACM Conference on Recommender Systems : Virtual Event, Brazil, September 22-26, 2020 (pp. 33–42). The Association for Computing Machinery. https://doi.org/10.1145/3383313.3412245
  • Jiang, B., Li, C., De Rijke, M., Yao, X., & Chen, H. (2019). Probabilistic feature selection and classification vector machine. ACM Transactions on Knowledge Discovery from Data, 13(2), Article 21. https://doi.org/10.1145/3309541
  • Open Access
    Li, C., & de Rijke, M. (2019). Cascading Non-stationary Bandits: Online Learning to Rank in the Non-stationary Cascade Model. (v1 ed.) ArXiv. https://arxiv.org/abs/1905.12370
  • 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
  • Open Access
    Li, C., & de Rijke, M. (2019). Cascading non-stationary bandits: Online learning to rank in the non-stationary cascade model. In S. Kraus (Ed.), Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence: IJCAI-19 : Macao, 10-16 August 2019 (pp. 2859-2865). International Joint Conferences on Artificial Intelligence. https://doi.org/10.24963/ijcai.2019/396
  • Open Access
    Li, C., Feng, H., & de Rijke, M. (2019). A Contextual-Bandit Approach to Online Learning to Rank for Relevance and Diversity. ArXiv. https://arxiv.org/abs/1912.00508v1
  • Open Access
    Li, C., & de Rijke, M. (2018). Incremental sparse Bayesian ordinal regression. Neural Networks, 106, 294-302. https://doi.org/10.1016/j.neunet.2018.07.015
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