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Results: 1,025
Number of items: 1,025
  • 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
    Zheng, J., Cai, F., Chen, H., & de Rijke, M. (2019). Pre-train, Interact, Fine-tune: A Novel Interaction Representation for Text Classification. ArXiv. https://arxiv.org/abs/1909.11824
  • 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
    Pei, J., Ren, P., Monz, C., & de Rijke, M. (2019). Retrospective and Prospective Mixture-of-Generators for Task-oriented Dialogue Response Generation. (v1 ed.) ArXiv. https://arxiv.org/abs/1911.08151
  • Open Access
    Baan, J., ter Hoeve, M., van der Wees, M., Schuth, A., & de Rijke, M. (2019). Do Transformer Attention Heads Provide Transparency in Abstractive Summarization? In Proceedings of FACTS-IR 2019 ArXiv. https://arxiv.org/abs/1907.00570
  • Open Access
    Olteanu, A., Garcia-Gathright, J., de Rijke, M., & Ekstrand, M. D. (Eds.) (2019). Proceedings of FACTS-IR 2019. ArXiv. https://arxiv.org/abs/1907.05755
  • Open Access
    Chen, Y. (2019). Learning for top-N recommendations: High-dimensional and heterogeneous information. [Thesis, fully internal, Universiteit van Amsterdam].
  • 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
    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
    Lin, Y., Ren, P., Chen, Z., Ren, Z., Ma, J., & de Rijke, M. (2019). Improving Outfit Recommendation with Co-supervision of Fashion Generation. In The Web Conference 2019: proceedings of the World Wide Web Conference WWW 2019 : May 13-17, 2019, San Francisco, CA, USA (pp. 1095–1105). Association for Computing Machinery. https://doi.org/10.1145/3308558.3313614
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